The Data Standard: Recent Episodes
The Data Standard
Listen to some of the top data professionals in the world speak on the latest innovations in the data field. Learn how machine learning and artificial intelligence are impacting the tech industries.
In this episode, guest Prashant Natarajan sits down with TDS to discuss this new book and applications in AI as well as data advice. Prashant Natarajan is the Vice President of H20.ai Health and Life Sciences division with a record of turning things around at Siemens Oracle Deloitte Unum. He is a Co-Faculty Instructor at Stanford University, author of numerous best-selling books e.g. “Demystifying Big Data & Machine Learning for Healthcare,” published by Taylor & Francis. His latest book is on its way " Demystifying Artificial Intelligence for the Enterprise: Building Tomorrow’s Self-Driving Organization (upcoming 2021)".
Connect with Prashant on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, we talk with Sam Anthony, the CTO, and co-founder of Perceptive Automata, a company that makes software to help autonomous vehicles understand human behavior. We discuss the missing piece for autonomous driving, why it is such a hard problem for autonomous vehicles to understand human intention and behavior, safety standards and testing for autonomous vehicles, Perceptive Automata’s business, how Perceptive Automata’s software works in ADAS and AV systems, how the algorithms are trained, and the state of autonomous vehicle development.
Connect with Sam on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Mickey Alon is a serial entrepreneur, passionate about designing, building, and launching innovative products that drive business outcomes. He’s Co-author of Mastering Product experience in Saas and CPO. Currently, he’s the CTO and Founder of Gainsight PX, a leading Product-growth platform. In this episode, guest Mickey Alon sits down with TDS to discuss Using data for marketing automation.
Connect with Mickey on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Ihsan Saracgil, Principal Data Scientist at Visible Alpha sits down with TDS to advise Ph.D. students in investment research.
Connect with Ihsan on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data science is an interdisciplinary field that extracts knowledge and insights from many structural and unstructured data, using scientific methods, data mining techniques, machine-learning algorithms, and big data. The healthcare industry generates large datasets of useful information on patient demography, treatment plans, results of medical examinations, insurance, etc. Data science provides aid to process, manage, analyze, and assimilate the large quantities of fragmented, structured, and unstructured data created by healthcare systems. This data requires effective management and analysis to acquire factual results. In this episode, guest Jonah Leshin sits down with TDS to discuss the importance of making data useable in healthcare. Jonah joined Datavant from Highland Math, where he was co-founder and Chief Data Scientist, leading data analytics and data monetization. Jonah holds a Masters in Math from the University of Cambridge, where he studied as a UK Fulbright Scholar, and a Ph.D. in Math from Brown University. Outside of work, Jonah enjoys playing tennis and taking family walks.
Connect with Jonah on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Antony Akisetty, Data Scientist & Global Search Strategist at Accuride International sits down with TDS to discuss their journey in the data science field and applications within small median manufacturing.
Connect with Antony on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Bilal Clarence sits down with TDS to discuss Data Privacy. Bilal is currently working at Capital One as Senior Director of Privacy and Data Solutions. Clarance was a member of the Pioneer men’s basketball team from 2001-2003 and the Bearcat men’s basketball team from 2003 to 2005, including the 2003-’04 squad that advanced to the NCAA Division II Elite Eight and was inducted into Northwest’s M-Club Hall of Fame in 2014. Continuing his basketball career after college, Clarance played basketball in Europe from 2005-2009. He was a member of the Danish men’s national team and served as captain from 2007 to 2009.
Connect with Bilal on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Jose Unpingco sits down with TDS to discuss Data sensitivity and defects as well as defining a health data paradox. Dr. Jose Unpingco is currently the Senior Director for Data Science/Machine Learning at West Health Institute in La Jolla, a nonprofit medical research organization. Dr. Unpingco earned his Ph.D. in 1997 from the Electrical and Computer Engineering Department at the University of California, San Diego. Prior to joining West Health, Dr. Unpingco worked with the SSC Pacific High-Performance Computing Center as an on-site Director for the DoD High-Performance Computing Modernization Program (HPCMP) in the PETTT component of HPCMP where he helped develop large scale file transfer technology that is still used today, as well as encouraging the DoD to adopt open-source technology such as Python for scientific computing.In addition to his work at SSC Pacific, Dr. Unpingco has extensive industrial experience as a research engineer and technical director at Hughes Aircraft Co., Raytheon, Mission Research, and ATK, working on a wide range of systems -- underwater acoustics, adaptive antennas, radar detection, and imaging, and modern target tracking. Dr. Unpingco is the author of two internationally published books by Springer titled “Python for Signal Processing” and “Python for Probability, Statistics and Machine Learning.” In addition to his duties at West Health, Dr. Unpingco is an invited lecturer at UCSD, teaching undergraduate/graduate Data Science classes. He also sits on the industry advisory council for UCSD Extension's Data Science and Machine Learning program.
Connect with Jose on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Nelson Tsaku sits down with TDS to discuss tips for business in data literacy and a crisp data model.
Connect with Nelson on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Milan Patel, Global Director, Data Science at ADARA, sits down with TDS to discuss analytical products that produce factual insights through low-cost high-value processes.
Connect with Milan on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Derek Singh, Chief Analytics Officer at FixtHub, sits down with TDS to discuss data modeling in a fixed income space.
Connect with Derek on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Telematics has been widely adopted in a wide variety of industries since the turn of the millennium and has provided businesses with previously unobtainable information into both vehicle and driver performance. This has drastically simplified fleet management processes and enabled significant improvements in efficiency and productivity. Vehicles are more than transportation: they’re now smart mobile devices generating large volumes of telematics data.
In this episode, guest Sajeewa Dayaratne sits down with guest host Ash Malgaonkar to discuss Data in the telematics industry.
Coretex is a complete telematics solution provider that supplies world-class fleet management and business intelligence technology, enabling transport operators to optimize the core of their business in real-time. The company’s enterprise IoT platform delivers cloud-based software and in-vehicle sensor technology. Coretex believes that technology should be used to create a safer, greener, and more productive society.
Connect with Sajeewa on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://ww w.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Samuel Gomez, CTO at GATACA, sits down with TDS to discuss systems transitions. GATACA is a cybersecurity company that develops self-sovereign identity technology to deliver hyper-secure, passwordless, and privacy-preserving access to digital services.
Connect with Samuel on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Tom Doyle, SVP, R&D at Medidata Solutions, sits down with TDS to discuss working with clinical trial software in medical data.
Connect with Tom Doyle on LinkedIn
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode of The Data Standard Podcast Experience, Philomena Lamoureux discusses Federated Learning and how it is impacting the technology sector in many different ways. She was formerly the Head of AI at Blooma.ai and currently is a Data Science Manager at ResMed. She has a strong background in federated learning systems and 10+ years of expert experience in computational modeling.
During Philomena’s PhD, she had a specialization in machine learning, natural language processing, and artificial intelligence solutions. She has a passion for data science and hopes to grow the data science community with her organization titled AI Paths. Her organization helps to bridge the gap between aspiring data scientists and industry related projects.
Connect with Philomena on LinkedIn
In this episode, guest Mark Cusack sits down with TDS to discuss cloud Data Warehousing. Yellowbrick Data is a 7-year-old startup that continues to grow in the highly competitive cloud data warehouse market. Yellowbrick recently raised $75 million in its latest round of capital funding as it expands into a variety of industries, including telecom, healthcare, retail, and manufacturing.
Yellowbrick describes itself as a cloud-native data warehouse. It is available for deployment on-premises and in hybrid cloud and multi-cloud environments.
Key topics from the interview include:
- What makes a database or data warehouse cloud-native? APIs, open-source, storage tiers, networking. How does Yellowbrick define it?
- One of the key things with cloud-native data warehouses is the separation of storage and compute. It gives you scalable storage and dynamic compute resources.
- Not all approaches to storage/computing are the same. Yellowbrick has published a white paper that defines six different levels of storage/compute separation.
- There are performance and workload advantages, but also important considerations around cost.
Mark Cusack
https://www.linkedin.com/in/macusack/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
We live in an information-centric world, those who have the information have the power. And while it may seem advantageous to constantly have your finger on the pulse of data flowing about your business and the industry, it quickly becomes a challenge to make something out of all those numbers and figures.
This is where data processing comes in: the capacity to research, collect, visualize and manipulate information to extract something useful from them. Control and understanding of large amounts of data is crucial to the success of a business, and data processing can help you reach the goals you’ve set for yourself easier.
But how exactly can data processing help a business?
In this episode, guest Kate McKenzie sits down with TDS to discuss the importance of data processing
Kate McKenzie
https://www.linkedin.com/in/kate-mckenzie-81388651/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The Data Standard is joined by Iwao Fusillo, Chief Data and Analytics Officer at General Motors. In this podcast, Iwao covers his journey through tech and how he began working at General Motors. He discusses empathy and mindfulness to his everyday life and workspace and how to become a mentor. He covers advice to his own daughter and others entering the tech field. He explains how data and analytics have become demoralizing over the pandemic and how we look at this data differently since this pandemic.
Product Data Science means building data products, tools and measurement strategies that impact the consumer using a rigorous statistical methodology, expertise, and experience. In this episode, guest Katrina Poole sits down with TDS to discuss Product Data Science.Katrina Poolehttps://www.linkedin.com/in/katrina-glaeser-poole-ab57a714/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Human resource departments are changing. What was an administrative function, running payroll and managing recruitment and training, is now a key player in corporate strategies and a major influence in employees’ everyday work experience. How has this come about? The answer lies in people analytics.
People analytics (PA) applies the power of artificial intelligence (AI) to the large data sets about people held by human resources in order to solve business problems. If a company has a problem retaining good staff, PA will tell them why and what to do about it. If sales in some shops are not as good as others, PA will identify the root of the problem in staff engagement so that the company can change managerial behavior.
The range of data available to PA includes not just HR staff records, but an increasingly wide range of data types that could have movement and health data from wearable devices. Using machine learning, HR departments can identify new trends and influence people's management decisions across the company.
The pitch of PA is that it replaces the vagaries of human intuition and professional experience with hard facts to create evidence-driven human resource management which brings massive efficiencies and benefits for the business.
The effects of the coronavirus pandemic on employment have accelerated the practice and influence of PA. The need for safe distancing at work and expansion of home working has increased the reach of HR and the amount of data available.
In this episode, guest Zach Frank sits down with TDS to discuss people Analytics and AI
Zach Frankhttps://www.linkedin.com/in/zachlfrank/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
What do space, art, and virtual reality have in common? In two words: Sasha Samochina. In this episode, guest Sasha Samochina sits down with TDS to discuss Data visualization in the immersive space. You’ll hear about Sasha’s last-minute choice to go to art school and the lightbulb moment that led her to merge her love of art and science.Sasha Samochinahttps://www.linkedin.com/in/sashasamochina/The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration. https://datastandard.iohttps://www.linkedin.com/company/the-data-standardhttps://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Stephen Drollinger, Director of Data Engineering at ICX Media, sits down with TDS to discuss his journey through tech, military life, and this company ICX Media.
Stephen Drollinger
https://www.linkedin.com/in/stephendrollinger/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Nikhil Goyal sits down with TDS to discuss which specializations are key to building an effective data team. Prior to LeafLink, Nikhil led the data science function for Gartner’s Marketing practice, gaining deep expertise in building scaled data products for large consumer brands. He has extensive experience in generating insights from e-commerce, search and transactional data leveraging experimentation, machine learning, and implementing business intelligence solutions. Nikhil has also held positions managing data science teams at and consulting F500 clients on marketing and advertising. Currently, Nikhil is responsible for continuing to evolve the data platform that powers the LeafLink marketplace.
Nikhil Goyal
https://www.linkedin.com/in/nikhilgoyal/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Management can make or break a workplace, as it is the most effective and organic way to raise productivity. Employees are usually more likely to have positive results under the right administration. There are many things that go hand-in-hand with good management. Great managers are a way of ensuring that the work that takes place somewhere will be a smooth ride to success. We can all attest to great bosses helping us thrive in our positions, but what really is it about them that makes them great? How are these people making sure that their workers stay happy while also managing to capitalize on it? Behind great management stand strategic thinkers. These are people that make strategic moves in a very humane way — they see their employees as actual people and learn to locate where their uniqueness and strengths lie. In this episode, guest Paul Carter sits down with TDS to discuss his philosophies of good management.
Paul Carter
https://www.linkedin.com/in/paul-w-carter/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Alessandro Pregnolato, VP of Data at Preply sits down with TDS to discuss business intelligence, big data, and his experience with running teams.
Alessandro Pregnolato
https://www.linkedin.com/in/alessandro-pregnolato-5472501/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
From chatbots, personalized recommendations on social media, traffic predictions, and virtual personal assistants including Siri and Alexa, advances in machine learning are becoming an integral tool that helps individuals navigate the modern world. Increased adoption of such technology across the world has driven massive growth in the volume of data, requiring businesses to harness the power of machine learning to make decisions, learn about and predict customer behavior to drive strategic advantage.
Combining the fields of engineering, statistics, mathematics, and computing, machine learning is one of the leading data science methodologies revolutionizing business. This course will cover a wide range of machine learning methods, both model-based and algorithmic.
In this episode, guest Pierce Freeman sits down with TDS to discuss ways of bringing ML data into practice.
Pierce Freeman
https://www.linkedin.com/in/pierce-freeman
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
When we think of computer science, namely Artificial Intelligence (AI), it’s easy to forget just how revolutionary it is.
Today, Artificial Intelligence can not only speak, write, listen and understand human language, it can also extract meaning from natural language to make informed decisions all thanks to Natural Language Processing. NLP is arguably one of the most exciting fields in AI and has already given rise to technologies like voice assistants, chatbots, translators, and many other tools that we use daily.
Natural Language Processing is a field of AI that enables computers to analyze, understand and arrange human language. Natural language processing software continues to advance to better interpret the nuance, context, and obscurities present within human communication.
NLP has already been adopted by many businesses that are driving results by drawing insights from large quantities of data while automating repetitive and monotonous tasks. NLP will only continue to benefit businesses as our reliance on, and understanding of, data shifts. With the amount of data at our disposal, it will be more and more pertinent to understand it, observe it, and in certain situations, censor it. Natural language processing will become more widespread in the years to come, as businesses reap the benefits it has to offer; from improving operations and reducing costs, to heightened customer satisfaction and more informed decision making. This episode features an interview with Kevin Wu, Chief Data Scientist at Consumer Edge. His company, Consumer Edge, enables its clients to obtain insights about the consumer from consumer transaction data.
Kevin Wu
https://www.linkedin.com/in/kevinwupublic/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Product teams are growing and with them a plethora of product suffixes: there are now product managers, owners, designers, analysts, strategists, and others all sitting on product teams. Product managers now also have more adjectives attached to their titles, whether it’s based on their seniority or their field, and as the discipline evolves, so will job descriptions. But there is one conspicuous function on many product teams today that doesn’t always have “product” in the title: data scientist. Data scientists facilitate data-based decision-making, experimentation, and innovation, key drivers that can put the product team ahead of the market. Being on the product team ensures they have alignment with- and a sharp focus on the product and business objectives.
In this episode, guest Martin Schmitz sits down with TDS to attempt to answer the question of does every product needs a Data Scientist?
Martin Schmidtz
https://www.linkedin.com/in/dr-martin-schmitz/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The allure of the cloud, with its promises of cost benefits, greater stability, and more recently as the lynchpin of digital transformation, is well understood. But if such promises are to be realized, tech leaders need to think beyond just lifting and shifting on-prem applications into the cloud. Companies are reprioritizing their cloud initiatives, many shifting toward multi-cloud architecture and away from more traditional infrastructure. Our guest on this episode, Amit Arora, Data Scientist at Hughes Network Systems, joins TDS to dive into this “massive paradigm shift” from a static to a dynamic world, where companies are expanding beyond the investment in their traditional data center into many other areas. We discuss the advantages of this shift as well as how to organize a successful transition from a people, process and technology standpoint. We also take a deep dive into data science and data governance.
Amit Arora
https://www.linkedin.com/in/amit-arora-539120a/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Organizations across the globe are looking to organize, process, and unlock the value of the torrential amounts of data they generate and transform them into actionable and high-value business insights. Hence, hiring data scientists – highly skilled professional data science experts have become supercritical. Today, there is virtually no business function that cannot benefit from them. In fact, the Harvard Business Review has labeled data science as the “sexiest” career of the 21st century. However, no career is without its own challenges, and being a data scientist, despite its “sexiness” is no exception.
Despite all the challenges, data scientists are the most in-demand professionals in the market. With the data world changing at a rapid pace, being a successful data scientist is not just about having the right technical skills but also about having a clear understanding of the business requirements, collaborating with different stakeholders, and convincing business executives to act upon the analysis provided.
If you’re a student or beginner facing challenges in the data science world and would like to learn more about overcoming them, then this podcast is for you as our guest Chester Isamay sits down with us to discuss challenges in the data science world.
Chester Ismay
https://www.linkedin.com/in/chesterismay/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The data in your data warehouse are only valuable if they are actually used. To make your data usable, you need to consider how the data are presented to end-users and how quickly users can answer their questions. In today’s world, businesses are continuously evolving. With changing times a wave of transformation be it digital, be it predictive forecasting, or building the agile ways of operations that will sustain in crisis, having your data structured in the right format and accurate with respect to changing needs of your business is of prime importance. Data modeling plays a crucial role in enabling business users to make more informed, and data-driven decisions are key to success. Data Modeling is a way to structure your data to be stored in a database, and the approaches define agility of the database, query performance and value add to the information being extracted. In this episode, guest Dr. Maria Wang sits down with TDS to discuss best modeling practices and also cover some guidelines on how to build better data models that are more maintainable, more useful, and more performant.
Dr. Maria Wang
https://www.linkedin.com/in/zmariawang/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Elliot Winard sits down with TDS to discuss concepts such as data and leadership.
Elliot Winard
https://www.linkedin.com/in/elliotwinard/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Productionizing your Machine Learning model is an important part of any machine learning project. Deploying machine learning models from training to production requires companies to deal with the complexity of moving workloads through different pipelines and re-writing code from scratch. In this episode, guests Scott Mitchell and Charlie Moad sit down with TDS to talk about productionizing machine learning models.
Scott Mitchell
https://www.linkedin.com/in/smitchelus/
Charlie Moad
https://www.linkedin.com/in/charles-moad/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Shalini Agarwal sits down with TDS to discuss ways of automating repetitive tasks, how we need more data scientists to make our applications smarter; however, we can make them more efficient and accomplish more with data scientists by having automated workflows and tools. These tools can be used by non-data scientists to leverage the established workflows and remove the repetitive tasks from the mountain of tasks expected from a data scientist. Shalini Agarwal is the Director of Engineering at LinkedIn, responsible for building core experience of Sales Solutions enterprise product. Before this, she was responsible for delivering scalable Search and Data Applications while managing a global team at LinkedIn. Shalini spent nearly a decade at eBay where she shaped buyer experience and transformed her career from individual contributor to management. She is leading LinkedIn’s REACH apprenticeship program since its inception, a program to hire talent coming from non-linear pathways to LinkedIn’s engineering team. She has been part of Women in Tech programs for over 10 years. Her passion lies in building great software, business applications, and empowering women.
Shalini Agarwal
https://www.linkedin.com/in/shalini-agarwal-5b735b2/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Rachael Weiss Riley sits down with TDS to discuss her work on the data for good space, and journey in providing support for mission-driven organizations. Rachael Weiss Riley leads Data Clinic’s strategic vision and oversees the translation of data science and technology support into lasting impact for our partner organizations. Prior to Two Sigma, Rachael spent nearly a decade engaging in geospatial research to measure the influence of the built and social environment on public health outcomes. She holds a DrPH in Epidemiology from the CUNY School of Public Health, an MPH from Hunter College, a BS from Brown University, and was recently appointed to the inaugural NYC Open Data Advisory Council.
Rachael Weiss Riley
https://www.linkedin.com/in/rachael-weiss-riley-891a134/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Our guest, Stas Zhukovskiy, explains that the Solutions Engineering team is there to help customers choose appropriate products for things like security, analytics, data management, and more. The products are laid out in guides and blueprints so the client can easily understand why products are chosen and how to use them. In this episode, guest Stas Zhukovskiy sits down with TDS to discuss his career in solutions engineering and the ins and outs of the industry.
Stas Zhukovskiy
https://www.linkedin.com/in/stzhuk/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
We don’t often think about how easy it is for humans to understand language. In everyday conversation, we convey meaning without considering how our brains translate so much unstructured data into useful information. For machines, however, understanding human speech and language is very hard. Natural language processing, or NLP, is a field concerned with enabling machines to understand human language.
In this episode, guest Sinan Ozdemir sits down with TDS to discuss the use of natural language processing in the industry. We focus on how to design and implement conversational AI algorithms, how to successfully integrate them, the hard and soft skills you need for a career in natural language processing, and more!
Sinan Ozdemir
https://www.linkedin.com/in/sinan-ozdemir/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data is the foundation of today’s business world. Each day, organizations get to interact with data concerning customers, vendors, security, and even employees. Luckily, it is those businesses that can separate the wheat from the chaff in their data mines that can harness the power that lies in data analytics. When used wisely, data can be a driver of change in your business, both by unveiling opportunities and pointing out problematic areas. This trickles down to how you collect and analyze your data. In this episode, guest Walt Gorman sits down with TDS to discuss the use of data in growing companies from a business owner's perspective.
Walt Gorman
https://www.linkedin.com/in/walt-gorman/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In today’s information-driven business environment, data is the fuel for growth. The more decision-makers know about their employees’ needs, changes in the industry, and the demands of customers, the more prudently they can strategize for future expansion. Big data has unlocked fresh possibilities, providing remarkable insights into market conditions and a heightened awareness of unfolding opportunities.
Collecting large quantities of data and finding analytical insights has become an integral part of how organizations of all kinds evaluate their progress and develop growth strategies. With the tremendous capacities for storing information in cloud-based solutions, businesses have the means to acquire a more detailed understanding of everything from the efficiency of manufacturing to the effectiveness of marketing campaigns.
Organizations can draw on data tools to discover areas that are currently ripe for improvement and garner a peek at the challenges and opportunities that lie ahead. With predictive analytics and machine-learning systems, businesses gain a sense of how existing problems or emerging ideas for growth will play out in the future. Those findings allow leaders to make smarter decisions and achieve long-term, sustainable success. In this episode, guest Dave Cook sits down with TDS to discuss how emerging companies should use their data.
Dave Cook
https://www.linkedin.com/in/cookdave703/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
As the Global Artificial Intelligence Lead and innovation lead within PwC’s Emerging Technology practice, Dr. Anand S. Rao is responsible for research and commercial relationships with academic institutions and start-ups, research, development, and commercialization of innovative AI, big data, and analytic techniques. With over 35 years of industry and consulting experience, he leads a team of practitioners who advise C-level executives and implement advanced analytics and AI-based solutions on a variety of strategic, operational, and ethical use cases. Drawing from his Ph.D. and research career in AI, as well as his subsequent experience in management consulting, Anand sits down with TDS to discuss the commitment to responsible ai.
Anand Rao
https://www.linkedin.com/in/anandsrao/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, we were honored to welcome as our guest Anita Ward, an applied anthropologist and Chief Development Officer of Salary Finance. Our conversation with Anita was about so much more than Anthropology and data. We talked about Salary Finance’s social purpose and how their work is bringing financial literacy and financial dignity to millions of people. Anita started by graciously sharing her emotional story of growing up without a home address. She got her first taste of financial empowerment from her first job at a McDonald’s in Las Vegas at just fifteen years old. Watching her parents struggle to find their financial footing, Anita knows firsthand the insecurity and taboo that surrounds families who experience financial hardship. She also shares new research that shows just how much employees’ financial stress is costing employers and what they can do about it. We’ll chat about how Salary Finance’s financial tools and borrowing options are helping employees rebuild their finances and their credit.
Anita Ward
https://www.linkedin.com/in/anita-ward-4567a39/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data, data, data — it’s long been a buzzword in the industry, whether big data, streaming data, data analytics, data science, even AI & machine learning — but data alone is not enough: it takes an entire system of tools and technology to extract value from data.
We have access today to more data than ever before. The question is: how do we make the most of it? For many, the biggest challenge lies in finding a data integration tool that can manage and analyze many types of data from an ever-evolving array of sources. But before that data can be analyzed or used, it must first be extracted. In this episode, guest Daniel Deychakiwsky sits down with TDS to discuss data extraction and digital signal processing.
Daniel Deychakiwsky
https://www.linkedin.com/in/danieldeychak
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Artificial Intelligence can be found in every aspect of our lives. From A-level grade predicting algorithms to Netflix recommendations, AI is set to change the choices we make and how our personal information will be used. In this episode, we explore AI techniques - limitations, its potential benefits, and harms - with our guest Carlos Cunha. Carlos received Ph.D. in astrophysics from the University of Chicago. Following a post-doc at the University of Michigan and a Kavli Fellowship at Stanford University, Carlos joined Bosch as a data scientist in 2014.
Carlos Cunha
https://www.linkedin.com/in/carlos-cunha-1121725/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
These days it’s a given that data needs to flow between systems, teams, and partners in order to deliver digital customer experiences and drive competitive insights – but very few companies take a strategic approach to governing these data flows across their business ecosystems. In this episode, guest Abhi Sharma sits down with TDS to discuss the ecosystem of data.
Abhi Sharma
https://www.linkedin.com/in/abhisharma/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Jason Hughes sits down with TDS to discuss how post 2020 has brought a separation of data analytics and data infrastructure. If you are daunted by the needs of your data infrastructure then it’s worth listening to how Jason and his team are approaching the problem.
Jason Hughes
https://www.linkedin.com/in/jasonhhughes/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Myles Guanzon sits down with TDS to discuss the ways that digital platforms are innovating the healthcare industry. Myles Guanzon is a servant engineering leader with a strong passion for data-driven, lean product development, Myles comes from a non-traditional engineering background. His career started in DevOps with server management and progressed by learning web development and co-founding a design agency to develop web applications for clients, including NASA. Today as the VP of Engineering at Omada Health, Myles leads the B2C teams that are responsible for engaging its members into lifelong health.
Myles Guanzon
https://www.linkedin.com/in/myles-guanzon-9ab50020/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Lon Baker, COO of VirtualPBX, has decades of experience in telecommunications, both as an entrepreneur and as a prominent figure of the company he now leads. His ambition and hard work have propelled VirtualPBX to be a global provider of voice, video, and texting services for businesses of all sizes. He has reshaped the way in which VirtualPBX serves its customers and has played a pivotal role in the company’s recent migration from its legacy platform of the 2000s to the current API-based Dash platform it now uses. There is no individual better suited to speak about data and cloud platforms.
Lon Baker
https://www.linkedin.com/in/lonbaker/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Scalability, scalability, scalability, scaling, these words represent the same concept: the ability for data processing systems to increase their processing capabilities as data increases. Scalability, therefore, corresponds to the ability of systems to evolve in order to process data of a different nature in large quantities and in always faster. If latency is taking too much progress and some internal or external customers are complaining about the slowness of your systems, it's time to focus on the issue of scalability. In this episode, guest Ken Tidwell sits down with TDS to discuss data scalability.
Ken Tidwell
https://www.linkedin.com/in/ketidwell/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data comes in many forms, all of it messy. Whether we’re talking about missing data, unstructured data, or data that lacks regular structure, you need methods to cleanse data before you can process it to improve its quality.
In this episode, guest Sean Gupta sits down with TDS to discuss data models, risk assessment, and machine learning role in the healthcare industry. Sean also discussed why machine learning predictions based on criminal history perform better than models based on DASH features.
Sean Gupta
https://www.linkedin.com/in/arijitseangupta/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guests Nathan Gould & Yotam Hadass sit down with TDS to discuss Building a startup data team.
Nathan Gould: https://www.linkedin.com/in/nathanegould/
Yotam Hadass: https://www.linkedin.com/in/yotamhadass/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Today's guest is Pranav Gandhi, Head of Business & Strategy Analytics at Signifyd. Founded in 2011 and headquartered in California's San Jose, Signifyd is the world’s largest provider of guaranteed fraud protection that enables online retailers to provide a friction-free buying experience for their customers.
Signifyd leverages big data, machine learning, and domain expertise to provide a 100 percent financial guarantee against fraud on approved orders that later turn out to be fraudulent. This effectively shifts the liability for fraud away from retailers, allowing them to increase sales and open new markets while reducing risk.
In today's episode, Pranav tells us about:
- Signifyd’s work in identifying fraud in the eCommerce sector
- How they are applying data science to solve these problems in eCommerce
- What attracted him to work for Signifyd
- How the pandemic has helped transform the customer experience
- What excites him for the future
Pranav Gandhi
https://www.linkedin.com/in/pranav-gandhi-55798029/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Ben Nichols is the Head of Product at IMS, Inc. Based in Liverpool, New York, IMS, Inc. is a fully integrated service provider of Conversational AI, Robotic Process Automation (RPA), Payments, Print, Electronic, and Mobile Communications.
Ben is also an Adjunct Professor of Data Science at Syracuse University, where he conducts lectures on Natural Language Processing, Database Design, and Scripting for Data Science.
Prior to that, Ben was Senior Director of Customer Insights at CB4, an AI tool that helps retailers uncover and fix the costliest in-store issues.
At CB4, Ben led a team of insights managers, sales solution architects, and data engineers who were responsible for multi-million dollar customer retention, customer upsells, and fulfilling new revenue goals.
Before CB4, Ben worked in multiple data intelligence and business analytics roles at organizations like IBM and Morgan Stanley.
In this exclusive episode, Ben Nichols shares with us the following aspects of his life and career:
- Talking from his past experience, he shares with us his views on the differences between working at a large organization vs working at a startup.
- What are the current capabilities of Natural Language Processing (NLP) and chatbots
- How cross-channel integration can be fostered using NLP for enhanced customer experience.
- What are the avenues of NLP Beyond chatbots?
Ben Nichols
https://www.linkedin.com/in/ben-nichols/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Zehra Hussain, Director of Engineering & Intelligence at Shippo , sits down with TDS to discuss How to establish Machine Learning in a business.
Zehra Hussain
https://www.linkedin.com/in/zehra-ali-a272583/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data drives the digital economy. Okay, that you know — but the big question is how to maximize your data and analytics efforts to both thrive as an organization and get an edge on the competition? What does it mean to be a truly data-driven enterprise? Gartner analyst Sumit Agarwal looks at the drivers for the rising importance of data and analytics.
Sumit Agarwal
https://www.linkedin.com/in/sumit-agarwal-4b45b71/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Insurance organizations have recently been navigating a number of talent shifts in a short amount of time. Organizations that did not previously have remote work strategies in place have had to quickly implement programs and launch new technologies to ensure business continuity in a virtual environment. For some companies, employees are continuing to work remotely, while others are seeing their workforces return to the office at a measured pace. Recruiting is being done in a primarily virtual environment and company culture is being redefined. As insurance organizations work to understand the short- and long-term impact of the evolving state of business on their teams, data and analytics can provide the insights necessary for navigating next steps and making informed talent decisions.
People analytics is at the crux of modern workforce management. Human resources departments operate as a strategic function, collecting workforce data and analyzing it in order to improve the performance of their business and influence their decisions and paths forward. Through data and analytics, HR teams can predict future workforce needs, identify flight risks, track career development progress, understand productivity trends and determine employee engagement levels, among many other metrics.
Karl Honerlaw, Assistant Director, Data Science at Liberty Mutual Insurance, sits down with TDS to discuss Talent analytics.
Karl Honerlaw
https://www.linkedin.com/in/karl-honerlaw-6916713b/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
There’s no doubt that there’s a growing need and reliance on data science in different industries and as a result the role of data scientists within organizations is becoming increasingly important. Of course, the definition of a data scientist and what this role typically encompasses varies greatly, and in light of this new trend, and in this podcast, we are speaking to Marty Belafsky, Vice President, Statistical Analytics and Data Science at Equifax, to learn a little bit more about data scientists and how the roles of data scientists have been elevated.
Mike Catanese
https://www.linkedin.com/in/mike-catanese-he-him-21a6412/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q ,
Do you know what your content knows?
As a Media and Entertainment company, you need to ask this question now more than ever since your industry will be creating 25% of all the content in the next few years.
If you process your content effectively, you can unearth insights and achieve better outcomes.
For media companies operating in today’s digital world, the workflows associated with producing content are more intricate than ever. Producing, managing, and distributing content is no simple feat, and metadata impacts all of those tasks. It’s no longer enough to distribute content on a single platform, such as print or television; increasingly, media companies are grappling with producing and distributing content for print, television, mobile applications, and the web. To respond, workflows and technologies have become more convoluted, with the complicated world of metadata lying under the surface of every workflow, technology, and piece of content. And, though metadata was once purely the domain of the tech team, today it affects everyone in a media organization—from editorial team members to business leaders. It can even impact a business’s bottom line. To help media professionals understand the key tenets of working with metadata—and to equip them to ask the right questions when making strategic and operational decisions—this podcast is for you.
Marty Belafsky, Data Strategy & Taxonomy at Amazon Studios, sits down with TDS to discuss metadata within media and entertainment companies.
Marty Belafsky
https://www.linkedin.com/in/marty-belafsky-3a80585/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
You’ve heard it a hundred times: Life will never go back to how it was before the pandemic. We’re in a “new normal,” from the way we work to how we get our groceries. On this episode of TDS, Ganesh Selvaraj, Data, Analytics, and AI Architect at WorkSafe New Zealand, digs into the impact of remote life.
Ganesh Selvaraj
https://www.linkedin.com/in/ganesh-selvaraj-87559844/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
To learn all about Data Science Products and the role they play in product management, this podcast is for you.
Product Data Science means building data products, tools, and measurement strategies that impact the consumer using a rigorous statistical methodology, expertise, and experience. A product-centric mindset is a paradigm shift for most data teams today. It changes people from being task-oriented and perhaps even simple outcome-oriented to being value-driven.
Nithin Ramachandran, Director, Data and Decision Science| Digital Capabilities at Kohler, joins TDS to discuss a product view to data science.
Nithin Ramachandran
https://www.linkedin.com/in/nramach/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, the executive team of Provenio.ai sits down with TDS to discuss use cases for ai automated productivity.
Dan Pace: https://www.linkedin.com/in/danpace/
Sriram Bhargav Madhav: https://www.linkedin.com/in/srirambhargav1978/
Ben Clannachan: https://www.linkedin.com/in/ben-clannachan-meng-a366379/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Rodrigo Senra, Group Technology Director at Work & Co, sits down with TDS to discuss more about what he does as well as working with distributed data.
Rodrigo Senra
https://www.linkedin.com/in/rodsenra/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Dan Knox, VP of Engineering at G2, sits down with TDS to discuss the pathway to startups and his own company G2.
Dan Knox
https://www.linkedin.com/in/dknox20/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Ben Garney sits down with TDS to discuss Social gaming.
Ben Garney is the founder of The Engine Company, a technical consulting firm providing services ranging from implementation to product architecture and development to fractional CTO. Ben has had exits as key hire, co-founder, and founder. His work has powered hundreds of millions of user experiences, been shown on the TED Prime stage, and used in planetary robotics research. He co-wrote a book, Video Game Optimization, and has done a technical review for a number of others. His areas of expertise include internet video, AR/VR, game engines, and engineering team leadership.
Ben Garney
https://www.linkedin.com/in/bengarney/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Cameron Gilmore, Director of Sales and Analytics at Blue Fire Leads sits down with TDS to discuss Data inspiration and sales tactics. In this video, you will gather a wide range of insights, tips, and advice on how you can increase your company’s sales numbers. They include things like why gratitude is so important in helping you and your team reach your sales goals, the importance of going beyond the numbers in motivating your team, why it is so important for leaders to get out from behind their desks, why you need to get to know your people, and why it’s important to set simple and achievable daily measurables. So what are you waiting for? Go ahead and check out the entire conversation with Cameron Gilmore. We’re confident that you will enjoy it!
Cameron Gilmore
https://www.linkedin.com/in/cameron-gilmore-57b32768/
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
When COVID-19 forced companies all over the world to send their employees home to work virtually, remote work had a big moment.
Yes, the rush to give employees access to all the tools they’d need to work from home was a bit, well, sudden for many employers. But after everyone settled in, what quickly became apparent to many office-based teams is
that employees could be productive and focused when not in the office—in many cases, even more so. Employers everywhere began to understand that remote work really works.
Listen in as we discuss why remote work isn’t just a fad in the workplace and how companies can build a great remote culture.
Vitor Zanetti
https://www.linkedin.com/in/vitor-zanetti-phd/
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Coming out of a stroke is not the only goal in today's
modern care, My guest David Golan is the CTO & Co-founder of Viz.AI,
their image AI technology is already transforming the way hospitals in
the U.S. identify and treat stroke patients, much faster and more
accurate saving both for the patient healthy cognitive days in his
future life and costs for the health system.
It was a pleasure to host David and listen to him explaining about the company, product, and strokes. In today’s show he explains why he is working on a system for automated stroke identification, and the engineering challenges in
building that system.
David Golan
https://www.linkedin.com/in/david-golan-1bb9ba98
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly
events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Jim Walker, Federal Chief Technology Officer at UiPath and former Deputy
Chief Information Officer at NASA joins the show to discuss the
evolution of robotic process automation in government. We also discuss
the many ways that RPA has been vital to the public sector’s shift to a
hybrid work environment, how the technology is supporting the future of
work, and how it has become an important tool. We also talked about ai
and ml chatbots.
Jim Walker
https://www.linkedin.com/in/jim-walker
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly
events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Rafael Alcarez sits down with TDS to discuss how
the pandemic shifted the way businesses leverage their data.
Rafael Alcarez
https://www.linkedin.com/in/rafaelalcaraz
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
With increasingly advanced and widespread data capture technologies and
applications, massive multi-source traffic data such as mobile
communication data, GPS data, AFC card data, Wi-Fi probe data, etc.,
provides valuable data resources for public transport operations. The
the recent idea of using big data technology to assist public transport
operations can help to achieve passenger analysis, passenger intelligent
control, and train operation systems.
Optimizing operations, cutting costs, and increasing revenues: These are the challenges facing almost every company in the public transportation sector. Companies that want to meet these challenges and ensure future success should utilize the potential of new technologies such as big data. Kim Martin, the Director, Infrastructure Data Science and Engineering at Netflix, sits
down with TDS to discuss data in the public transportation space.
Kim Martin
https://www.linkedin.com/in/kimberlynicolemartin/
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Building a product from scratch involves a sequence of processes
starting from preparing a framework and applying the findings to design a
model to iterating for the final result and putting it in a data pipeline. At TDS, Piya Mohapatra, Director, Data Science at Monster,
discusses ways of building big data products from scratch, key skills required, challenges to overcome, and more. Piya specializes in leveraging analytics to build products.
Piya Mohapatra
https://www.linkedin.com/in/piyamohapatra
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Dennis Wakabayashi sits down
with TDS to discuss how the world of social media is about to change.
Dennis is VP of the world’s 7th largest marketing solutions company
where he is responsible for the strategy and execution of integrated
marketing -- also known as customer experience (CX) for Fortune 500
companies.
In May 2020 he was named a top CX expert of the decade and ranks among the top 150 CX influencers globally. He regularly
hosts/emcees marketing industry events appears on international
podcasts and is a renowned public speaker, author, and educator. He has
more than 50,000 social media followers and is dedicated to empathy,
collaboration, and growth for customers and brands.
Dennis Wakabayashi
https://www.linkedin.com/in/denniswakabayashi
TheData Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Have you ever thought about how could you cluster data? Whether one
categorizes emails or performs customer segmentation, clustering is most
of the time the way to go. This approach consists of dividing the
dataset into groups (or clusters) such that objects belonging to the
same cluster are more similar than items belonging to different
clusters. It is possible to calculate such similarity according to a
specific metric that of course can change with the problem to be solved.
Daniel Gremmell, Head of Data at Policygenius, sits down with TDS to
discuss cluster techniques.
Daniel Gremmell
https://www.linkedin.com/in/daniel-gremmell-6953842b
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly
events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Marketers deliver tremendously, and often unrecognized,
value to their business. Yes, you read that correctly: unrecognized.
Value is a complex concept that makes it hard to measure and even harder to showcase throughout an organization. The digital age is awash in data that demonstrates the power of marketing to build a brand, produce engagement, generate leads, and boost revenue. So why do marketers still
struggle to prove their value and demonstrate ROI?
In the Digital Age, businesses need to effectively track and monitor their
marketing performance, and leverage analytics and reporting to grow
their business.
Marketers deliver tremendously, and often unrecognized, value to their business. Yes, you read that correctly:
unrecognized. Value is a complex concept that makes it hard to measure
and even harder to showcase throughout an organization.
The digital age is awash in data that demonstrates the power of marketing to build a brand, produce engagement, generate leads, and boost revenue. So
why do marketers still struggle to prove their value and demonstrate
ROI?
Gregory Hooven, President at MarketReach, sits down with TDS to discuss the lack of leveraging metrics in marketing.
Greg Hooven
https://www.linkedin.com/in/greghooven
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
With the focus on innovation and technology in
Chattanooga over the last decade and the proliferation of shipping and
logistics startups, it shouldn't come as a surprise to see a company
burst onto the scene the way Freightwaves has. If you haven't heard of
them, this podcast episode featuring Daniel Pickett, Chief Data
Scientist at Freightwaves should serve as a great introduction.
In In this episode you'll hear a discussion about geospatial data, data
intelligence, financial markets, the shipping, and logistics industry.
Daniel Pickett
https://www.linkedin.com/in/daniel-pickett-cfa-7363974
The Data Standard is a community of data scientists, architects, engineers, and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io
https://www.linkedin.com/company/the-data-standard
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Social media usage has skyrocketed in recent years, but never more so than it has since the COVID-19 outbreak, as lockdowns restrictions shifted user behavior and habits towards more digital dependency. While
data science has certainly played a significant role in social media
and vice versa, the pandemic has forever altered the impact and
importance of analytics in this space. Social media platforms have become a playground for real-time trend analysis and the focal point for modern business marketing strategies. Today we have an incredible discussion with Benjamin Kepner about the more nuanced and in-depth nature of applying data science to your social media.
Benjamin Kepner
https://www.linkedin.com/in/benjaminkepner/
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Behavioral Data Science is a new, emerging, interdisciplinary field,
which combines techniques from the behavioral sciences, such as
psychology, economics, sociology, and business, with computational
approaches from computer science, statistics, data-centric engineering,
information systems research, and mathematics, all in order to better
model, understand and predict behavior. With massive amounts of data
currently available and being collected, obtaining access to data is
seldom the concern. Information is being produced and stored at an
unprecedented rate, and increasingly, much of the big data
being collected is about human behavior. Our behavior is captured in the
information that we provide from our smartphones, computers,
televisions, smart speakers, credit cards, or tracking devices from
insurance companies. Sifting through this data and deriving insights on
human behavior enables organizations to make more effective decisions
and develop stronger policies.
Edward Chenard
https://www.linkedin.com/in/edwardchenard/
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly
events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Furtado talked about her science, technology, engineering, and
mathematics background, and how her education at the U.S. Air Force
Academy and the Massachusetts Institute of Technology prepared her for a
career designing systems ground troops use to communicate with
aircraft. Furtado is the portfolio lead at the Air Force’s Kessel Run.
Jazmin Furtado
https://www.linkedin.com/in/jazminfurtado/
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly
events, publish through leadership pieces, and offer a stimulating
ecosystem for networking and collaboration.
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The Data Standard Presents, an E-Commerce Panel Event, Join the Data
Standard and two speakers explain E-Commerce during the Pandemic.
Guest speakers:
James Stewart - https://www.linkedin.com/in/jamesmdst...
Maria Wang - https://www.linkedin.com/in/zmariawang/
Companies: Realtor.com and Harvard Business Review
The Data Standard is a community of data scientists, architects, engineers,
and enthusiasts. In addition to regular podcasts, we host monthly events, publish through leadership pieces, and offer a stimulating ecosystem for networking and collaboration.
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Technology runs our lives these days. Smartphones,
tablets, and computers – we really can’t seem to function without them.
In a very short amount of time, technology has exploded in the market
and now, many people cannot imagine a life without it.
To understand how we left the dark ages (which really wasn’t all that long
ago) to where we are today, it is important to understand how technology
evolves and why it matters. Brian Thomas, Chief Technology Officer at
Coruzant Technologies, sits down with TDS to discuss the Evolution of
Technology and his journey in the tech field.
Brian Thomas
https://www.linkedin.com/in/brianethomas1/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
RudderStack is an open-source Customer Data
Infrastructure for collecting and routing your customer data for
analytics. With a special focus on data privacy, security, and
reliability, RudderStack is enterprise-ready and gives you the
flexibility of transforming your event data to suit your business
requirements.
In this interview with TDS, Soumyadeb Mitra – the
founder, and CEO of RudderStack – talks about the Customer Data
Infrastructure space, making data engineers the heroes of their
companies and RudderStack.
Soumyadeb Mitra
https://www.linkedin.com/in/soumyadeb-mitra/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data and analytics are essential for anticipating the future and
responding proactively to changing trends in the dynamic world of
education. Stuart Jones, President, Chief Executive Officer at Acorn
Evaluation, sits down with TDS to discuss Data in the education sector.
Stuart Jones
https://www.linkedin.com/in/stuart-jones-acorn/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
How can you drive interest and revenue for a business
in the equipment segment? Businesses in this realm work in competitive,
business-to-business focused segments where generating leads and closing
sales requires overcoming much greater inertia.
Equipment marketing and advertising strategies then have to be effective enough to reduce the time/budget cost of conversion.
If your company sells construction equipment, heavy machinery, or
industrial supplies then understanding the role of digital marketing is
crucial to being able to grow. Digital marketing strategies like search
engine optimization, paid advertising, email outreach, and content
optimization are crucial to growing brand recognition and capturing new
leads.
Growing revenue is important to organizations throughout
the world, yet there are infinite ways to achieve this elusive goal.
Whether you're focused on attracting more customers or increasing the
lifetime value of your customers, marketing is a vital component of your
business operations - while also being one of the most contentious.
Executive leadership may look to marketing as one of the first places to cut in
difficult times, while other technology leaders may not fully understand
the value that marketing brings to the organization. With data-driven
marketing campaigns, you are able to more effectively communicate the
importance of marketing to the company by tying specific campaigns to
tangible business results.
Steve Smith
https://www.linkedin.com/in/stevesmithequipmentfx
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Software developers are the people most targeted by hackers conducting
cyberattacks against the technology industry, with the hackers taking
advantage of the public profiles of individuals working in the
high-turnover industry to help conduct their phishing campaigns. Sal
Kimmich, Developer Advocate at Sonatype, sits down with TDS to discuss
cybersecurity attacks on developers.
Sal Kimmich
https://www.linkedin.com/in/sarakimmich/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Together with 5G, the Internet of Things, and cloud computing,
artificial intelligence is radically reshaping the telecommunications
landscape in an era of advanced digitization and high-speed
technological development. Whether the rapid rise of AI will impact, or,
even, disrupt most of the industries is no longer up for debate. And
the telecommunication industry is no exception. Markets and Markets
predict the global market for artificial intelligence in the
Telecommunication industry to reach a staggering amount of $2.5 billion
by 2022. Surprisingly, the onset of AI, Data Science, and Machine
Learning will allow Telecom companies to achieve better performance,
make investments as well as profit additionally. Telecom operators will
be able to create additional revenue streams for themselves by exploring
business niches they haven’t previously. AI-embedded technologies can
be a useful tool in the telecommunications industry. Implementation of
AI by telco companies resulting in the development of highly
personalized products, improved fulfillment processes, and enhanced
network management, allows telecommunications operators to provide their
customers with more attractive services as well as enhance their
customer retention. Salih Ergut, Chief Data Science and R&D Officer
at OREDATA, sits down with TDS to discuss AI within the telecom
industry.
Salih Ergut
https://www.linkedin.com/in/ergut/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Being a great data scientist is mostly about the way in which you
approach problems. Data scientists apply the scientific method in the
commercial environment, which is why scientists can often successfully
transition into the field. This sounds simple enough in theory, yet many
scientists with superb academic backgrounds find it difficult to make
the move into industry. We reached out to Mehmet Alpaslan leader in the
data science and analytics communities who made the leap from academia
to industry and asked for his advice on how he transitioned out of
academia and into the data science industry.
Mehmet Apsalan
https://www.linkedin.com/in/mehmet-alpaslan/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
On today’s podcast, JD Martindale talks about his role as Director of DS
at Anthem, gives us some inside details on the latest milestones in
speech and language technology, and explains how mastering speech
recognition, translation and conversation will move machines further
along the path from “perceptive AI” to “cognitive AI” and that much
closer to truly human intelligence.
JD Martindale
https://www.linkedin.com/in/jd-martindale/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Danica Westgard sits down with Laura Edell from
Annielytics to discuss going back to the office early during COVID and
her journey as a woman in the data field.
Connect with Laura and Danica on LinkedIn
Laura Edell - https://www.linkedin.com/in/lauraerinedell/
Danica Westgard - https://www.linkedin.com/in/danica-westgard-2210a1b2/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Operational and Analytical Data Systems are both very similar in how
they provide information on your organization, company, or non-profit,
but the two are very structurally different and provide different types
of insights. That might seem a little confusing, so in this episode,
we're going to discuss operational and analytical data.
Joshua Masia
https://www.linkedin.com/in/joshua-masia
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Liora David sits down with TDS to share her
thoughts on remote work-life, her career journey, and advice she would
give to young women in the tech field or those aspiring to be in the
STEM field.
Liora David
https://www.linkedin.com/in/liora-guy-david-phd-98147129/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
There is little debate about the importance of ethics in health care,
and clearly defined rules, regulations, and oaths help ensure patients'
trust in the care they receive. However, standards are not as well
established for the data professions within health care, even though the
responsibility to treat patients in an ethical way extends to the data
collected about them. Increasingly, data scientists, analysts, and
engineers are becoming fiduciarily responsible for patient safety,
treatment, and outcomes, and will require training and tools to meet
this responsibility. Healthcare privacy is a central ethical concern
involving the use of big data in healthcare, with vast amounts of
personal information widely accessible electronically. In this episode,
guest Eugene Day sits down with TDS to discuss his work in the
healthcare data field, as well as some research Seattle Children's
Hospital, has done surrounding biases and ethicality within healthcare
data.
Eugene Day
https://www.linkedin.com/in/geneday/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Have you seen real estate listings that describe a
house as architect-designed? It adds a lot to the asking price, but
aren't all houses designed by architects? Most are, but they're then
rather generically churned out by a construction company. If your house
counts as architecture, though, someone designed it for specific needs
and tastes.
In the same way, your organization stands to benefit
when your data architecture is put together based on your particular
data management and analytics needs. But often, we inherit many of the
generic components and integrations from the product designs of our
technology vendors. If we've customized some of the structure of data
architecture, that may have happened ad hoc, over a long time.
Within a successful data architecture, a conceptual design based on the
business process is the most crucial ingredient, followed by a logical
design that emphasizes consistency, integrity, and efficiency across all
the databases and data pipelines. Once the data architecture is
established, the organization can see what data resides where and ensure
that the data is secured, stored efficiently, and processed accurately.
Also, when one database or a component is changed, the data
architecture can allow the organization to assess the impact quickly and
guides all relevant teams on the designs and implementations. Lastly,
the data architecture is a live document of the enterprise systems,
which is guaranteed to be up-to-date and gives a clear end-to-end
picture. In summary, a holistic data architecture that reflects the
end-to-end business process and operations is essential for a company to
advance quickly and efficiently while undergoing significant changes
such as acquisitions, digital transformation, or migration to the
next-gen platform.
Derek Doel
https://www.linkedin.com/in/derekdoel/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Microfinance is a service where financial institutions
back small start-ups and would-be entrepreneurs with small loans,
oftentimes referred to as microloans. Such initiatives are most popular
in the poorest parts of the world.
In this business model, big
data is used to assess a customer’s creditworthiness. Big data is
defined as large volumes of structured and unstructured consumer data
that can be gathered from a user’s entire profile of online activity, be
it on social media platforms, product purchases, or electronic
check-ins.
Such data is usually collected from various data
points, which vary according to the type of online activity performed.
An example of this is phone usage data which includes call duration as
well as the frequency of calls.
It is this kind of data that will
then be used to assess a customer’s ability to repay a loan provided via
a microfinancing scheme. What is used is not the direct content of the
data, but rather the behavioral patterns associated with the data
collected.
Big data analytics is an increasingly integral part of
the tech ecosystem and is fast disrupting the financial services
industry as well. The ability to transform raw data into meaningful
insights is the cornerstone of cross-industry development.
Mansoor Ahmad
https://www.linkedin.com/in/mansoornano/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Your quarterback goes down, and you need a new one. So,
you look at the stats on the site to find a guy who had a good couple
of weeks. Plus, you saw an interview with the guy, and he seems nice.
You just have a feeling about him, so you pick him up and add him to
your fantasy football roster. You may have made a mistake.
Picking a player while letting your emotions play a factor is not going to mean
you failed completely. Plenty of people have had successful teams with
this method. However, using data science to evaluate the potential of a
player for the rest of the season is more likely to give you an edge.
Data still typically beats your gut feeling.
Kevin Day, Founder at Fantasy Football Calculator, sits down with TDS to discuss the data behind fantasy football.
Kevin Day
https://www.linkedin.com/in/kday33/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In an ideal world, startups progress through inflections of growth and
success as customers require more enhancements or features that are
needed on a larger scale. The startup’s engineering team has to grow to
address these different dimensions and do it with increasing pace and
predictability. Scaling an engineering team can seem like a mighty feat.
A growing company is going to be in need of a growing engineering team
to keep up with the demands of the job. Whether you need three or 30
engineers on your team, it is important that you take the necessary
action to get qualified and experienced engineers on your team.
Jeremy Eastwood
https://www.linkedin.com/in/jeremy-eastwood/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Over the past few years, Data Science and Analytics have become
popularized and more and more ingrained in every aspect of our lives.
Data science has spread to almost every industry, but there are still a
few where it has just hit the surface, one of which is the gaming
industry and the impact of it is growing very fast. Human-oriented games
are now evolved into data-oriented games.
The gaming industry is
on its rise nowadays. With more than 2 billion players all over the
world gaming industry is a resource of enormous revenues and these
revenues are expected to grow further on. With a growing number of
users, the amount of data to proceed is enlarging. Users’ playing time,
interaction time, quitting point, peaks of activity, results, scores,
etc. present vast material for analytics.
The use of Data in
gaming is to make strategies according to the behavior of the player and
constantly collecting data and making predictions and decisions. The
new generation of gaming is dependent on data collection by analyzing
the behavior of the player and the use of Artificial Intelligence and
Machine Learning for better development.
Francisco Rius, Head of
Data Science - Minecraft at Microsoft, sits down with TDS to discuss the
intersection between art and science.
Francisco Rius
https://www.linkedin.com/in/franciscorius/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The COVID-19 pandemic and the resulting stay-at-home orders have led to
significant changes in the way people work. One of these changes
involves the increased use of video conferencing as a means of
communicating or holding work meetings. In this episode, guest Hisham
Hamadeh sits down with TDS to discuss ways that the pandemic might have
helped transform how we identify and commercialize treatments for other
illnesses.
Hisham Hamadeh
https://www.linkedin.com/in/hisham-hamadeh-5a342ba/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
As companies collect more and more data, the ultimate
goal is to translate this data into insights that can help them optimize
business performance. For example, they may wonder which of their
customer segments is most profitable? How they can reduce their customer
acquisition costs? Which features of their flagship product are
underutilized or need to be enhanced? Which of their best employees are
potential flight risks? In most cases, answering one of these questions
will lead to . . . more questions.
When the questions you can ask the
data are unlimited but the time and resources to find the answers
aren’t, you need a strategy for how you query the data for meaningful
insights. We often like to say, “There’s no such thing as a stupid
question.” However, when it comes to analytics, some questions can be
poorly phrased, ill-conceived or misguided. They can lead to costly,
time-consuming expeditions into the data that don’t yield any actionable
insights.
The French philosopher Voltaire said, “Judge a man by
his questions rather than his answers.” This same standard can be
applied to organizations. Companies that struggle to get meaningful
insights from their data are often not asking the right questions. The
better the quality of your questions, the more valuable your insights
will be. Preparation is a key success factor to querying data
effectively and discovering meaningful insights.
Alexander Finn
https://www.linkedin.com/in/alexanderfinn/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Carlton Sapp is the Managing Vice President for the Data Analytics for
Technical Professionals team. Dr. Sapp sits down with TDS to talk about
all things AI. In addition to managing the data analytics team in
Gartner for Technical Professionals, Dr. Sapp provides guidance on
systems engineering, digital engineering, digital threads, digital twin,
model-based systems engineering, edge intelligence, artificial
intelligence, machine learning, modern data management strategies, data
ingestion strategies, streaming analytics, data integration, and IoT
analytics. Dr. Sapp provides data-driven insights and design strategies
based on more than 25 years of practical project experience and
research. He is known for using systems thinking approaches to solve
complex technical and business challenges. In previous roles, Dr. Sapp
designed digital assets, agent-based systems, digital twins, data
analytics architectures, advanced analytics architectures, data
integration strategies, distributed compute systems, service-oriented
architectures, event-based architectures, and machine learning
algorithms.
Carlton Sapp
https://www.linkedin.com/in/drcarltonesapp/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data scientists continue to be in high demand, with companies in
virtually every industry looking to get the most value from their
burgeoning information resources. As organizations begin to fully
capitalize on the use of their internal data assets and examine the
integration of hundreds of third-party data sources, the role of the
data scientist will continue to expand in relevance. This role is
important, but the rising stars of the business are those savvy data
scientists that have the ability to not only manipulate vast amounts of
data with sophisticated statistical and visualization techniques, but
have a solid acumen from which they can derive forward-looking insights.
So what does it take to be data science whiz?
Pranav Sharkarn
https://www.linkedin.com/in/pranav-shankar/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Today’s TDS episode is all about data and data models, and why they
matter. Deciding how to model your data ahead of time can pay off down
the road. It helps ensure that the people who are using the data get
what they need from it, and can reduce technical debt. Data modeling is a
way of mapping out and visualizing all the different places that a
software or application stores information, and how these sources of
data will fit together and flow into one another. This is a hugely
important stage in the design process for any business-critical IT
system. When developers are figuring out how a new system will work,
they establish what the most pressing needs of a business are, what kind
of data they’ll need to access in order to meet those needs, and how
the data will be used.From there, they can start to create a diagram (or
model) of how each pocket of data will flow into each other, and how
they’ll interact.
Sean Robinson
https://www.linkedin.com/in/seankrobinson/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
An early stage start-up is basically a company which is still in the
development phase. These are start-ups which are growing and working
towards the day when they will be successful. Early-stage is a term used
to characterize a startup business venture. It generally concerns the
phase of startup development generally preceding the rapid growth phase.
The early stage is characterized by activities such as research
development, marketing research, and product business development. This
is considered by entrepreneurs, investors, and researchers to be the
riskiest stage in the startup lifecycle. The probability of success of
the venture depends heavily upon actions taken during this stage. During
this phase, consumers (or the customer market) will be called to
evaluate and compare the price, quality, and feasibility of the business
value proposition. Nicolas Bertagnolli, Co-founder and CTO at mpathic,
sits down with TDS to discuss early stage startups.
Nicolas Bertagnolli
https://www.linkedin.com/in/nicolas-bertagnolli-058aba81/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data monetization is the process of using data to increase revenue.
Direct data monetization involves selling direct access to your data to
third parties. You can sell it in raw form, or you can sell it in a form
that’s already transformed into analysis and insights. Typical examples
may be contact lists of potential business prospects or findings that
impact on buyers’ industries and businesses. Indirect data monetization
is where things get interesting. Firstly, there’s data-based
optimization. This involves analyzing your data to reveal insights that
can improve your organization’s business performance. Data can identify
how to reach customers and understand customer behavior so you can drive
your sales. Data can also highlight where and how to save costs, avoid
risk and streamline operations. Secondly, there are data-driven business
models, where you use your data to discover new business opportunities
and customers. You can embed analytics into your products or services,
providing advantages for you and your customers. Customers benefit from
direct access to usage analytics and other data generated by each
product they already use. You benefit from offering this as a value
add-on or as a new tier of service, encouraging customer loyalty. In
turn, you get a better insight into how your customers are using your
products. Without the right data monetization strategies in place, you
risk missing critical insights that could improve your business. With
the necessary strategies in place, you are well equipped to sharpen your
competitive edge.
Patrick Callinan
https://www.linkedin.com/in/patrick-callinan-051b46/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Part of effective client management and retention is knowing how to
communicate effectively. When it comes to official business matters,
every opportunity to interact with your clients must be on point. You
want to meet your client’s wants and needs, providing them with
information that’s important to them while also valuing their time.
Naturally, the client report plays a vital role in communication.
Reports are a tool for conveying results clearly, and they support
transparency by putting you and your client on the same page. When done
right, reports keep your client engaged and committed to meeting your
shared goals. Unfortunately, many people fail to take advantage of their
report’s potential. This leads to the chronic problem of boring
reports—10-page documents filled to the brim with soporific text and
statistics. Sure, reports aren’t exactly known for being the most
riveting of reads. But with a bit of visual design and thoughtful
presentation of data, even the most numbers-heavy report can be
interesting to your clients. In this podcast, we’ll go over a few ways
to take your client reporting to the next level.
Peter Jaffe
https://www.linkedin.com/in/peter-jaffe-4b18a66/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
A repetitive way of collecting, retaining, and using data proficiently,
securely, and in a cost-effective way. The main challenges with data
management goals are to help individuals, businesses, and associated
things enhance the use of data within the limits of strategy and
regulation so that they can make choices and take actions that make the
most of the benefit to the companies. A vigorous data management plan is
becoming more important than ever as organizations increasingly depend
on elusive properties to create worth. Data Governance is the
cornerstone of every successful data management program, but it is often
associated with suffocating rigidity, great cost, and unclear ROI. How
can we get it right? Today we speak with Amrutha Rajendra to find out!
Amrutha Ajendra
https://www.linkedin.com/in/amrutharajendra/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Parag Sharavista, Data Leader at HP Enterprise sits down with TDS to discuss the 3 data tracks.
Parag Sharavista
https://www.linkedin.com/in/pshr/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Marissa Arciola, Senior Director of Mobile Customer Base Management
Strategy at Altice USA sits down with TDS to discuss building data sets
from scratch.
Marissa Arciola
https://www.linkedin.com/in/marciola/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
While leading BI vendors target large audiences with their analytics
tools, many other companies target a single specialized industry and use
their expertise to best serve users. Artificial Intelligence is now
penetrating almost every existing domain. Finance, healthcare,
education, transportation and many sectors are witnessing active use of
AI. This intelligence is now being used for an upcoming niche:
prediction of consumer tastes and food trends. Spoonshot, a startup
based in Bangalore, is using AI to help businesses operating in the food
and beverages sector serve their customers better by providing useful
insights on future food trends and guest intelligence. Sai Sreenivas
Kodur is the Co-Founder & CTO of Spoonshot, a technology startup
supporting food innovation intelligence. Sai is specialised in compilers
and machine learning, with a working experience in internet technology
companies solving the problems of search and recommendations. Sai worked
at Zomato, India's largest food ordering and restaurant discovery
platform, as a Software Engineer in search, where he re-built its search
relevance and ranking models from scratch to improve restaurant
results. Later he worked at Myntra, India's biggest online fashion
store, as a Senior Software Engineer, leading search and style services
and working on various technological functions. Currently, he is
spearheading engineering and data science at Spoonshot to build an
innovation intelligence and analytics platform for the Food &
Beverage industry.
Sai Sreenivas
https://www.linkedin.com/in/sai-sreenivas-k-7b748b13/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The digital age, the age of information, the computer age – all are
terms used as identifiers to depict how the 21st century has brought
with it nearly unfathomable amounts of data. Knowing that the
information is there and how to access it is one thing, but making sense
of it and using it for both defense and commercial purposes is what
makes it so-called big data. The challenge for both warfighters and the
manufacturers that provide them with their technology: Acquiring that
data in contested environments and relaying it in an efficient way.
Making this task more difficult is the reality that conflict often
occurs in data-denied areas, making it near-impossible for these systems
to access the information the military wants or doesn’t yet know it
needs. The accessibility of data in-theater is a key challenge for
advancing big data utilization in the military. Big data is a broad term
with applicability across many areas of interest to the military. We
see a clear trend of military requirements directing the use of big data
throughout the life cycle of new procurements and the modernization of
legacy systems. As new sources of data develop and novel uses for data
emerge, big data growth will continually outpace utilization in all
industries, including the military. Big data has been called the oxygen
of the ML revolution and military intelligence gathering. The
capabilities are designed to supplement each other with the intent to
provide warfighters with mission-critical, timely information at the
tactical edge.
Mark Zais
https://www.linkedin.com/in/markzais/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In the insurance industry, big data is the name of the game. It provides
valuable insights into all facets of company operations and performance
– from consumer behavior to underwriting practices to the ROI of
marketing campaigns. Companies that want to leverage that information
into actionable insights turn to big data analytics. Big data technology
has created an endless stream of opportunities, which have resulted in
an increase in its usage – especially in the insurance and insurtech
industry. Overall, big data in the insurance industry has helped
businesses make processes more efficient, save on costs, predict
behaviors to develop better products, and increase productivity. And big
data technology isn’t going anywhere anytime soon. Join TDS and Kevin
Mahoney as he discusses how analytics helps the insurance industry.
Kevin Mahoney
https://www.linkedin.com/in/kevin-mahoney-37342757/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Whether you are organizing a training session for your colleagues or
planning to construct a huge engineering plan, project management will
help you achieve what you need to do. Project management is the way we
apply knowledge and processes to work in order to complete that work in
the smoothest way possible. Ultimately, we are using tools, methods,
skills, techniques, and the experience of the team to achieve the
objectives set for the work. Projects have a clear goal, which means we
can plan how to get there and work through a structured plan to ensure
that the goals are achieved. Any complex project that a company
undertakes has a better chance of achieving its goal, vision, and the
desired results if the team executing the project employs both the
science and art of project management. The science you can learn and
apply because there are many courses, books, tools, techniques, and
software packages out there that help you understand how to manage your
project from a methodological perspective. Learning the art of project
management on the other hand is a different story because it takes
experience to know what you need to do when you need to do it, and how
much of it to apply to a given situation.
Christine Abanilla
https://www.linkedin.com/in/christine-abanilla-ms-pmp-csm-acp-05a0a251/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Predictive analytics is a branch of advanced analytics
that makes predictions about future outcomes using historical data
combined with statistical modeling, data mining techniques, and machine
learning. Companies employ predictive analytics to find patterns in this
data to identify risks and opportunities.
Predictive analytics is
often associated with big data and data science. Companies today are
swimming in data that resides across transactional databases, equipment
log files, images, video, sensors, or other data sources. To gain
insights from this data, data scientists use deep learning and machine
learning algorithms to find patterns and make predictions about future
events. These include linear and nonlinear regression, neural networks,
support vector machines, and decision trees. Learnings obtained through
predictive analytics can then be used further within prescriptive
analytics to drive actions based on predictive insights.
James Stewart
https://www.linkedin.com/in/jamesmdstewart
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Big data gives us eyes and ears into our marketing initiatives. It
captures insights into our prospects and customers at a level of detail
never before possible. We can respond to real-time audience actions and
drive customer behavior at the moment. Big data is transforming
marketing and sales in ways that were unachievable just a few years
ago. Placing an advertisement in a newspaper or magazine may be a great
way to raise awareness of your brand, but can you prove the
effectiveness of that advertising spend? In the past, very few marketers
have been able to tie offline activities to revenue, but with
developments in data-driven marketing attribution, they’re making vast
leaps forward. This means that decisions no longer have to be guided by
speculation and assumptions, but rather by hard facts - highlighting the
importance of big data in marketing. With data-driven marketing
campaigns, you are able to more effectively communicate the importance
of marketing to the company by tying specific campaigns to tangible
business results.
Ashley Stryker
https://www.linkedin.com/in/ashleyrstryker/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Big data is disrupting everything it touches, but automotive is probably
one of the top industries that enjoy the benefits and leverages it
provides to the fullest. The applications of big data in the automotive
industry are numerous and each of them seems to launch a wholesome new
niche within the market. The automobile industry is being transformed by
the adoption of technologies, applications, and services ranging from
sensors to artificial intelligence to big data analysis; thus, the
ecosystem is witnessing a steady influx of new players, resulting in the
continuous evolution of the future car. Furthermore, big data
analytics have helped automobile manufacturers boost their efficiency in
terms of sales and marketing. It has also improved its operations by
aiding in the incorporation of utilities like predictive maintenance and
service schedule. It has also aided automotive vendors in streamlining
the procurement process, making it more cost-efficient by analyzing the
data for demand prediction. Ryan Barton, Chief Analytics Officer at
Barnes Crossing Auto Group sits down with TDS to discuss data in the
automotive industry.
Ryan Barton
https://www.linkedin.com/in/ryanwbarton/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
When you’re thinking about starting a company or first in the
entrepreneurial trenches, any nugget of advice you can get from someone
who’s been there before is like gold. But as time goes on, you’ll
realize that some of those tips are better—and more applicable to your
business—than others. Some founders learn on the fly. Others study at
business school. Then there are those who receive a piece of advice at
some point in their career that ultimately shapes everything they do.
Mike Nemke
https://www.linkedin.com/in/mikenemke/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
As we enter into the digital age, data science has been growing rapidly
into a vital field that has revolutionized many disciplines along with
our everyday lives. Data science integrates a plethora of disciplines to
produce a holistic, thorough, and insightful look into complex data,
and helps to effectively sift through muddled masses of information to
extract knowledge and deliver actionable insights and innovations.
There are lots of great things about working in data science. But like
any job, being a data scientist can be frustrating — especially when
your company isn’t taking the right approach to big data. Brandon
Pinzon, Chief Security Officer at Argo Group sits down with TDS to
discuss Challenges and recommendations for data science grads.
Brandon Pinzon
https://www.linkedin.com/in/bpinzon/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Fraud analytics is the use of big data analysis techniques to prevent
online financial fraud. It can help financial organizations predict
future fraudulent behavior, and help them apply fast detection and
mitigation of fraudulent activity in real-time.
More people are using
online banking or managing their finances online every year. In 2020,
the worldwide lockdown due to COVID19 convinced even more customers to
use online banking for at least a portion of their financial activities.
Fraud analytics applies machine learning techniques to financial data.
Machine learning is a subset of Artificial Intelligence (AI). Where AI
is the computer implementation of a human-like thought or
decision-making process, machine learning uses mathematical algorithmic
techniques to extract complex relationships within the data being
analyzed. Fraud analytics uses machine learning to examine all the
pertinent data regarding a transaction and assigns a risk score to the
transaction. Based on the risk score it makes a recommendation to allow
the transaction, block the transaction, or ask for step-up
authentication before allowing the transaction. And this can all be done
in real-time with or without human intervention, providing the
financial institution with enhanced fraud prevention without causing
undue friction in the customer session. Every transaction, from login to
logout, can be examined for potential fraud risk. Data science is part
of the solution. Financial Institutions collect huge amounts of
behavioral, device and transactional data. Analysis of this data by the
fraud detection system and/or fraud investigations team can be used in
the prevention and detection of financial fraud. But the analysis will
only be as good as the data in the data set. With good data, there are a
number of big data analysis techniques that a machine learning-based
fraud analytics system can use to combat financial fraud. Predictive
analytics looks at patterns to make predictions on future, heretofore
unknown events to understand the potential or propensity for fraud.
Pattern recognition and anomaly detection identifies events that don’t
conform to expected patterns. Machine learning algorithms can learn from
the data and make predictions on future events.
Harry Lu
https://www.linkedin.com/in/chinhengharrylu/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Streaming data, i.e., frequently changing and potentially infinite data
flows, are becoming more and more prevalent in today's interconnected
world. In a Smart City context, for instance, citizens can access
real-time information about a city's weather, pollution, or traffic
conditions. However, turning vast real-time data streams into actionable
knowledge poses significant challenges. Igor Moiseev, Sr. Director of
Engineering at Standard Cognition sits down with TDS to discuss how he
spent his pandemic time as well as his thoughts on the infinite data
stream.
Igor Moiseev
https://www.linkedin.com/in/moiseevigor/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The pandemic has forced the adoption of new ways of working.
Organizations must reimagine their work and the role of offices in
creating safe, productive, and enjoyable jobs and lives for employees.
Velizar Shulev, Co-founder, CTO at ClaimCompass, and Inbal Budowski Tal,
Senior Director of Machine Learning at Pendo.io, sit down with TDS to
discuss their thoughts on their productivity levels throughout the past
year and ways they are re-imagining their thinking.
Velizar Shulev
https://www.linkedin.com/in/vshulev/
Inbal Budowski Tal
https://www.linkedin.com/in/inbal-budowski-tal-7115a61/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Pradyumna Upadrashta, Chief Data Science Officer at Mastech InfoTrellis
sits down with TDS to discuss his thoughts on intelligence architecture.
Pradyumna Upadrashta
http://linkedin.com/in/pradsu
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Artificial intelligence and Machine Learning are benefiting a wide range
of industries, and the manufacturing sector is the one that is listed
at the top. Advances in technology through machine learning (ML) have
provided an opportunity to accelerate innovation processes and improve
decision-making. Nowadays, most businesses across the globe are adopting
machine learning solutions in manufacturing to improvise their
processes and getting better results.In metals manufacturing, the
operations environment is full of data collected by thousands of sensors
at a very small interval. Historically, decision-making was based on
traditional descriptive analytics techniques. However, with the advent
of Machine Learning and AI is quickly becoming an important
decision-making tool. Novelis, through models deployed within melting
and rolling operations, has already seen a great value from these
techniques.
Amit Dingare
https://www.linkedin.com/in/amitdingare/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Nowadays, many companies are inclined to carry out advanced machine
learning solutions along with custom AI solutions to stand tall in the
competitive market. Analytics is essential to improve the bottom lines
so that you can increase the efficiency of your business. With machine
learning and AI, it is effortless to get some comprehensive strategies
for analytics that will help you to run your business successfully. With
a view to that, you must include the machine learning strategies in the
data structure. Lalit Wadhwa, is our guest in this episode. He is the
EVP & Chief Technology Officer at Encora, a leader in the large and
rapidly growing outsourced product development market. Lalit, brings a
lot of insights about machine learning and Ai. His core experience as a
hardware product engineer shines through this episode, as he talks about
machine Learning and AI use cases This is a great episode, pointing out
a few challenges that can be resolved with focusing on Data at all
levels in the enterprise, let's dive in.
Lalit Wadhwa
https://www.linkedin.com/in/lalitwadhwa/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Artificial Intelligence (AI) and Machine Learning (ML) systems are
increasingly being used across all sectors and societies. Alongside this
growth, model fairness has been gaining awareness over the past years.
This field aims to assess how fair the model is when treating
pre-existing biases in data. Fairness in machine learning is an exciting
and vibrant area of research and discussion among academics,
practitioners, and the broader public. The goal is to understand and
prevent unjust or prejudicial treatment of people related to race,
income, sexual orientation, religion, gender, and other characteristics
historically associated with discrimination and marginalization, when
and where they manifest in algorithmic systems or algorithmically aided
decision-making. AI systems are enabling new experiences and abilities
for people around the globe. Beyond recommending books and television
shows, AI systems can be used for more critical tasks, such as
predicting the presence and severity of a medical condition, matching
people to jobs and partners, or identifying if a person is crossing the
street. Such computerized assistive or decision-making systems have the
potential to be fairer and more inclusive at a broader scale than
decision-making processes based on ad hoc rules or human judgments. The
risk is that any unfairness in such systems can also have a wide-scale
impact. Thus, as the impact of AI increases across sectors and
societies, it is critical to work towards systems that are fair and
inclusive for all.
Simi Manchanda
https://www.linkedin.com/in/sweetee-simi-m-0189861b/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Data Science, Machine Learning (ML), and Artificial
Intelligence (AI) have without doubt become hot topics across all
industries, including healthcare. Companies, large and small, are
rushing to stock up on data scientists, but are data scientists alone
enough to build a successful data science practice in healthcare?
Without a doubt, data scientists are needed to build models. Thanks to
the increasing availability of genomics and other biomedical data, many
machine learning approaches have been proposed for a wide range of
therapeutic discovery and development tasks.
In the era of eHealth
and personalized medicine, “big data” and “machine learning” are
increasingly becoming part of the medical world. Algorithms are capable
of supporting diagnostic and therapeutic processes and offer added value
for both healthcare professionals and patients.
Cristian Regep
https://www.linkedin.com/in/cristian-regep-9269ab2b/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Andy Hendrick sits down with TDS
to discuss trucking technology, the evolution of transportation
management systems, what they're good for, where gaps exist, and some
thoughts on where they're headed in the years to come. With 25 years in
the supply chain and over 14 of those years in trucking technology
working with hundreds of companies, Andy lives and breathes the
transportation industry. Andy has been a featured speaker at numerous
supply chain conferences, and has provided insights and thought
leadership for leading trucking and supply chain publications based on
those hands-on implementation experiences around the globe.
Andy Hedrick
https://www.linkedin.com/in/hedrickandy/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Digitization in the finance industry has enabled technology such as
advanced analytics, machine learning, AI, big data, and the cloud to
penetrate and transform how financial institutions are competing in the
market. Large companies are embracing these technologies to execute
digital transformation, meet consumer demand, and bolster profit and
loss. While most companies are storing new and valuable data, they
aren’t necessarily sure how to maximize its potential, because the data
is unstructured or not captured within the firm. As the financial
industry rapidly moves toward data-driven optimization, companies must
respond to these changes in a deliberate and comprehensive manner.
Efficient technology solutions that meet the advanced analytical demands
of digital transformation will enable financial organizations to fully
leverage the capabilities of unstructured and high-volume data, discover
competitive advantages, and drive new market opportunities. In this
episode of The Data Standard, Paul Camuto, VP of Data and Integrations
of Broadridge, reflects on how data in the financial services industry
has evolved over the past few decades.
Paul Camuto
https://www.linkedin.com/in/pcamuto/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Startup companies can come in all forms, but the phrase “startup
company" is often associated with high growth, technology-oriented
companies, many of which seek to disrupt an existing market or to create
a new market. Investors are generally most attracted to those new
companies distinguished by their risk/reward profile and scalability.
Tech startups are early-stage businesses that aim to develop and
manufacture technological products or services. They focus on bringing
these products or digital services to the markets. They have been
emerging in recent years and becoming valuable companies. However, on
the other hand, there are also many tech startups that fail. Thus, it is
important to understand how a tech startup can succeed.
Ido Shlomo
https://www.linkedin.com/in/ido-shlomo/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Today's guest is Niamh Vianney Muldoon. Niamh is an
experienced self-starter with extensive Information Security risk
management experience. She is currently the Global Data Protection
Officer at OneLogin, who the leader in Unified Access Management,
Enabling Organizations to Access the World. They make it simpler and
safer for organizations to access the apps and data they need anytime,
everywhere.
In the show, Niamh will tell you about:
How she got into Cybersecurity
The exciting roles she has enjoyed over the years
The importance of mentoring
Success stories of moving into the world of IT
Data Governance
The exciting work at OneLogin
Niamh Muldoon
https://www.linkedin.com/in/niamh-vianney-muldoon-b2174853/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
User Empowerment means providing the users with the
capability to alter the aspects of the services that affect either the
user experience or the outcomes of the services. That can come in form
of pseudo-governance, where users are provided with some limited
decision-making capabilities.
It can also be argued that the
User-Centric approach extended with customization capabilities covering
user experience and the parts of execution about which user can have
material or emotional interests should also be qualified as User
Empowerment. Jim Mcpherson, VP Enterprise Data at InComm Payments, sits
down with TDS to discuss User empowerment & New technologies in the
field.
Jim Mcpherson
https://www.linkedin.com/in/jim-mcpherson-b580396/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The pandemic is disrupting every aspect of our health care system.
Chelsea Dubie reflects on the need for a data and health IT
infrastructure to address the who, what and how for these current
unprecedented times and for the new reality that will follow. The
COVID-19 (coronavirus disease 2019) pandemic has underscored the
critical need for all countries to strengthen their health data and
information systems and ensure the routes the data travel, from
submission to use, are unobstructed. Timely, credible, reliable, and
actionable data are key to ensuring that political decisions are
data-driven and facilitate understanding, monitoring, and forecasting.
Chelsea Dubie
https://www.linkedin.com/in/chelsea-dubie-4a0b9327/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Women are the key piece to the puzzle of realizing the highest maturity levels of digital enterprises. AI is one of the fields in which women can experience tremendous success, especially with the right push towards female participation in the industry. Women are a necessary force that organizations must integrate in order to accelerate the AI maturity of enterprises. Lisa Woodley Vice President, Customer Experience, and Theresa Kushner Consultant, AI/Analytics at NTT DATA sit down with The Data Standard to discuss women in data driven tech industries.
Lisa Woodley
https://www.linkedin.com/in/lisawoodley/
Theresa Kushner
https://www.linkedin.com/in/aristotle-socrates-9066271b/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
James Bullard, CTO at Pendulum Therapeutics (formerly Whole Biome), sits
down with TDS to talk about the use of technical tools in different
companies and industries.
James Bullard
https://www.linkedin.com/in/james-bullard-a2960a61/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Quantum computing and machine learning are not a match made in heaven. But in the world of humans, opposites do attract, and similarly, both these sciences requiring completely different
backgrounds and skills are intrinsically related when it comes to driving futuristic technologies. Of course, the extent of influence that quantum computing will have on AI remains an open question. Still, most experts believe quantum computing will alter AI significantly in the times to come – probably even make it more humane and efficient.
Machine
learning and artificial intelligence have emerged as two key areas of research for applying quantum computing algorithms. The natural synergies between the two fields could change the future of data science in several ways, which are discussed in this episode.
Devin Chatterji
https://www.linkedin.com/in/devin-chatterji-129b746/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Traditionally we think about value in business in terms of
assets—property, plants, equipment, inventory, and even human resources.
The explosion of technology over the last decade has made us re-think
what is valuable. In fact, what many businesses today consider to be
their most valuable asset cannot be held in your hand because it is the information generated
by the collection of billions of bits of data. In fact, the data that
businesses gather about their customers is, to the most progressive
companies, invaluable! This podcast sheds some light on how businesses
can use the information to gain a competitive advantage. As you can see,
the use of information cuts across the entire organization. Although
the uses may vary from area to area one thing that is consistent is that
the use of accurate, timely information can improve business processes
and thereby enhance the customer experience. When the customer
experience is enhanced, revenues rise, profits rise, and business
flourishes. Information is quickly becoming the lifeblood of business
and its importance in the long-term success of an organization cannot be
overstated.
Peter Sheldrick
https://www.linkedin.com/in/peter-sheldrick-0039ab2/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
With more statistically rigorous analytic methods to further automate
insight identification, data science and machine learning can help
health systems align effective measures with specific improvement goals
more accurately and faster than typical data analysis. Health systems
can decrease the risk, cost, and time associated with outcomes
improvement and accelerate the process by using data science to help
determine which measures will help them meet their goals for their
specific populations. As the industry continues to work toward outcomes
improvement, leading organizations will rely on data science and machine
learning to test hypotheses, identify opportunities faster and more
accurately, and ensure that their improvement measures support their
overall goals.
Patrick McGill
https://www.linkedin.com/in/patrick-mcgill-md/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Advances in digital technologies and data analytics have created
unparalleled opportunities to assess and modify health behavior and thus
accelerate the ability of science to understand and contribute to
improved health behavior and health outcomes. Digital health data
capture the richness and granularity of individuals’ behavior, the
confluence of factors that impact behavior at the moment, and the
within-individual evolution of behavior over time. These data may
contribute to discovery science by revealing digital markers of
health/risk behavior as well as translational science by informing
personalized and timely models of intervention delivery. And they may
help inform diagnostic classification of clinically problematic behavior
and the clinical trajectories of diagnosable disorders over time. The
COVID-19 pandemic has fundamentally altered health priorities around the
world. Across all sectors, organizations are engaging with digital
solutions to tackle the spread of the virus and relying on data to make
critical decisions around healthcare delivery and resource
prioritization. In this podcast, we will discuss why we are seeing an
increase in the use of digital during the COVID-19 pandemic, and how
this extreme experience has awakened the world to the crucial
infrastructure that needs to be in place in order to rapidly respond to
future health emergencies.
Shashank Garg
https://www.linkedin.com/in/shashank-garg0403/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The intelligence demonstrated by machines is known as Artificial
Intelligence. Artificial Intelligence has grown to be very popular in
today’s world. It is the simulation of natural intelligence in machines
that are programmed to learn and mimic the actions of humans. These
machines are able to learn with experience and perform human-like tasks.
As technologies such as AI continue to grow, they will have a great
impact on our quality of life. It’s but natural that everyone today
wants to connect with AI technology somehow, may it be as an end-user or
pursuing a career in Artificial Intelligence. Advances in artificial
intelligence are likely to herald an unprecedented period of rapid
innovation and technological change, which will fundamentally alter
current industries and the economy. What is different to previous
periods of technological progress is the speed at which these
developments are happening and the extent to which they will shape
markets around the world. How will they affect prosperity and
inequality? How can AI be deployed for the greater good and to improve
economic outcomes?
Sarah Hoffman
https://www.linkedin.com/in/sarahfhoffman/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Nearly all businesses around the world have undergone an organizational
change in one way or another during the last year. As nations begin to
heal, talks of the “new normal” beyond the pandemic are starting to look
like a realistic possibility rather than a far-off dream. For many
businesses, it is unclear what this post-pandemic working world might
look like. However, change is on the horizon, and managing this next
stage effectively will either make or break an organization. In order to
make this transition as smooth as possible, businesses need to
implement compelling and practical Change Management strategies that can
guide them through this next phase. Michael Gonzales, Chief Data
Scientist at Prolifics, sits down with TDS to discuss his views on
companies jumping too quickly into reformative changes.
Michael Gonzales
https://www.linkedin.com/in/michael-gonzales-231b9085/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
Most marketing teams are leaving a lot of money on the
table. Brands are collecting an extensive amount of data at various
stages of the customer journey. Data science helps us leverage this data
into actionable insight that results in a greater return on
investment.
Data science methods like machine learning,
clustering, and regression have moved marketing from a creative domain
to a scientific one. By leveraging data science, marketing teams can
extend their top-funnel approach to incorporate the full-funnel and
uncover product and customer insights at scale in an unprecedented way.
To do this, growth marketers should understand what data scientists can
and cannot do as well as some of the methods and how marketing teams use
data scientists.
Alexander Liss
https://www.linkedin.com/in/aliss77777/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
In this episode, guest Matthew Busbee sits down with TDS to discuss the
decisions his company is making in regards to moving data to cloud
platforms as well as choosing whether to delete data.
Matthew Busbeeb
linkedin.com/in/mbusbee
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
In the midst of a global COVID-19 pandemic, a top priority for many
pharma and biopharma companies is to get a vaccine developed, produced,
and delivered to the public as quickly as possible. Ushering a vaccine
through rigorous testing protocols and regulatory approvals is not an
easy (or quick) effort, but incorporating advanced data analytics could
help accelerate the process. Data analytics has proven effective in
speeding vaccine development both by enabling more efficient Design of
Experiments (DOE) and by creating rapid-scale production rollout
processes. Tomasz Adamusiak, Director of Data Science at Pfizer sits
down with TDS to explain what his company, Pfizer, is doing with the
vaccine as well as what a designed vaccine is.
Tomasz Adamusiak
https://www.linkedin.com/in/adamusiak/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
Aristotle Socrates, Head of Data at TextNow, sits down with TDS to
discuss his views on machine learning, ai, and what he deems was the
most important trend of the last 20 years.
Aristotle Socrates
https://www.linkedin.com/in/aristotle-socrates-9066271b/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Gal Klein (CTO) is the co-founder of Audioburst. We discuss analyzing,
segmenting, packaging and making talk audio content discoverable in
real-time. Audioburst is doing this daily on millions of minutes of
radio and podcast content and the same technology could be applied to
social audio.
Gal Klein
https://www.linkedin.com/in/gal-klein-026873a/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Eitan Anzenberg, Chief Data Scientist at Bill.com, sits down with TDS to
discuss his work life, mentorship, and kindness within the valley
community.
Eitan Anzenberg
https://www.linkedin.com/in/eitan-anzenberg-5639b444/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Today's guest is the great and brilliant Dr. Pavel Dmitriev, VP of Data
Science at Outreach.io. This AI-driven sales engagement platform has
raised over $250 million since founded in 2011. We talk about all
things. Sales engagement- and one thing- that's really interesting in
this podcast- is how we get better at doing sales engagement. Sales
engagement is not simple for a variety of reasons. Approaching one cold
prospect in a way that increases the chance of their conversion is
challenging enough — handling the logistics of hundreds or thousands of
leads is exponentially harder. That’s why software platforms with email
marketing automation features—outreach among them—serve to simplify the
process. There are plenty of solutions for sales management that provide
autoresponder features, but the real question is—are these templated
responses organic enough to enable high conversion rates?
Pavel Dmitriev
https://www.linkedin.com/in/paveldmitriev/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
Discussions about learning to code and working as a programmer often
focus on the perks and benefits associated with the field—things like
flexible job schedules, high pay (even for entry-level positions), and
opportunities to work remotely. But what about the job itself? From the
outside looking in, coding can seem like endless hours of typing
gibberish onto a computer screen—a task that, quite frankly, sounds
pretty boring. Do coders put up with fundamentally boring work just to
get those perks and benefits? Or is the work of coding significantly
different than what a newcomer might think? To get a solid answer, we
spoke with Cary Huang. The short answer to the question “is coding
boring?” is—quite simply—”no.” Of course personal preferences can vary,
but coding is so not boring for so many people that you’ll even find
coders jumping to the profession from much flashier sounding
backgrounds.
In this episode, guest Cary Huang sits down with TDS to
discuss what he does to make coding an exciting thing to watch. We tried
to round up some essential tips to help you have fun while programming
in this podcast.
Cary Huang
https://www.linkedin.com/in/cary-huang-119637139/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
In this episode, guest Matt Thompson sits down with TDS to discuss his pandemic work-life experience.
Matt Thompson
https://www.linkedin.com/in/matt-thompson-98355651/
The Data Standard
https://datastandard.io/
https://www.linkedin.com/company/the-data-standard/
https://www.youtube.com/channel/UCTuolowXD05RY9DkIWqRT6Q
The perils of running a startup are often talked about, whether it’s trying to secure funding, marshaling the tech you need, or establishing your go-to-market strategy - but no company can remain a startup forever. Eventually, every startup needs to try and grow beyond its current stage, undertaking the difficult journey to scale its operation without falling apart at the seams.In many ways, the scale-up stage is the ‘tricky second album’ of corporate operations and is fraught with new and distinct pitfalls than those faced by founders in the early days of a company’s lifecycle. This week, we’re joined by Richard Smaldonet and Elizabeth Cook, to discuss how companies can effectively meet the challenges of becoming a scale-up.Richard Smaldonehttps://www.linkedin.com/in/elizabeth-cook-444ba7b/Elizabeth Cookhttps://www.linkedin.com/in/rsmaldone/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guests Rita Arens & Kristen Harris from H&R Block sits down with TDS to discuss using data to improve human help in viral settings.Rita Arenshttps://www.linkedin.com/in/ritaarens/Kristen Harrishttps://www.linkedin.com/in/kristen-harris-171b134a/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Graham McDonald, Chief Data Officer, Associate VP, Technology & Data Science at Urban Institute sits down with TDS to discuss the nonprofit research world.Graham McDonaldhttps://www.linkedin.com/in/graham-macdonald-a1124510/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Jacob Adler Data Analyst at dutchie sits down with, TDS to discuss dutchie the company and data science at Caesars Entertainment. Jacob Adlerhttps://www.linkedin.com/in/adlerjacob/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest David Relyea sits down with TDS to discuss whether Signal is here to stay or if we are moving towards different communication. David Relyeahttps://www.linkedin.com/in/david-relyea-44120557/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Ghost kitchens are proving to be a resilient model that will be ever-present into the future. But what is a ghost kitchen, exactly? And could a ghost kitchen or virtual brand be the right strategy for your operation? In this episode, we chat with Veho's Strategy & Operations Manager, Tyler Spitz, about the evolution of foodtech, how ghost kitchens could help address food delivery apps' remaining barriers, and how pandemic-era shifts might impact our dining options and experiences into the future.Tyler Spitzhttps://www.linkedin.com/in/tylerspitz/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
No code tools have taken over formerly code-only sectors of the tech industry. Everything from website building, to app creation, game development, software platforms, and automation can all be created and built by individual makers and a robust set of no code software platforms and tools. The final frontiers - for now! - of no code seem to lie within virtual and augmented reality and artificial intelligence. With so many companies trying to simplify, quicken, or achieve no code in the field of developing artificial intelligence applications, it’s clear that AI and no code are slowly coming together. We’re excited for a future where anyone can build AI applications. A future where small businesses can compete with large companies and where marketing, design, and customer service teams can build the data science tools they need. This is also a world where bias does not exist in artificial intelligence applications and companies can outsource their needs to individual creators and makers. This is not a far off dream and we’re excited to be part of the no code revolution in AI.Chandra Khatrihttps://www.linkedin.com/in/ckhatri/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
LLNL biostatistician Nisha Mulakken has enhanced the Lawrence Livermore Microbial Detection Array (LLMDA) system with detection capability for all variants of SARS-CoV-2. The technology detects a broad range of organisms—viruses, bacteria, archaea, protozoa, and fungi—and has demonstrated novel species identification for human health, animal health, biodefense, and environmental sampling scenarios. She discussed the project on this video episode of The Data Standard Podcast.Nisha Mulakkenhttps://www.linkedin.com/in/nishamulakken/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Over the last several weeks, we’ve spoken to experts working on various aspects of the machine learning pipeline–from data wrangling to programmatic data labeling to specialized AI hardware. In today’s episode with ASRC's Chief Data Scientist Aaron Dant, we discuss one of the central components of the machine-learning pipeline, deep learning models. In particular, we consider the novel challenges that arise as people get serious with deep learning, the crucial role of startups in tech, and the excitement surrounding deep learning projects.Aaron Danthttps://www.linkedin.com/in/aaron-dant-32365a160/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Data literacy is the ability, confidence, and willingness to engage with data to acquire information, construct or review analyses, and communicate insights to inform decisions. It is distinct from proficiency. The data literate are not quantitative prodigies but are familiar with the methods used to create models from data, apply a critical eye to any insights derived from data, and communicate those findings to inform decision making. Being data literate is essential for executives and managers to enact a data strategy that will succeed in their organizations. And, it is achievable through self-learning, training, expert consultation, and building relationships.Andrew Bateshttps://www.linkedin.com/in/andrewgbates/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
ATLAS’s Brad Bode shares how he built his business and what he’s planning. Brad is the CTO & CIO of Atlas SpaceAtlas Space is a developer of a cloud-based command and control system designed to gather information from space for use on the ground. The company's ATLAS Freedom software platform simplifies the communications services for Space 2.0 with the software space management and control system, enabling businesses to gather information from the satellite to the antenna and then to the customer and streamline the system for accessing data.Brad Bodehttps://www.linkedin.com/in/brad-bode-1381826/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Why should you earn an technical certification (or certifications)? What is the value of an technical certification to you and to your employer? A technical certification is a quick and readily recognized benchmark mapped to a specific skill set based on standardized testing. A certification demonstrates your dedication, motivation and technical knowledge on a specific platform. Once you earn an certification, you join a select group of individuals - a peer group with demonstrated skills. Having a certification shows that you not only possess comprehensive knowledge of that technology but you also care enough about your own career to spend the time and money to get certified. Remember: You are your own best career manager!Dr. Bradley Jensenhttps://www.linkedin.com/in/bradley-jensen-a9a7404/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Whether it's using prediction modeling for finding the best route on your way to work or having a, albeit possibly imprecise, conversation with Siri or Alexa to remind you to buy more toilet paper, we have almost daily contact with a myriad of technologies. Some applications might seem small or somewhat insignificant, but many of these technologies that we almost take for granted are being used in the real world to help people achieve fantastic things. Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world’s most pressing challenges and deliver positive social impact. Kapil Kochharhttps://www.linkedin.com/in/kapil-kochhar-33037952/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Very often, organizations focus a lot on data cleansing after the data has been captured. But any incremental effort spent on focusing on data quality at the source will reap long term benefits. Data quality is on the top of everyone’s mind recently, but getting it right is as challenging as ever. One of the contributing factors is the number of people who are involved in the process and the potential impact on the business if something goes wrong. In this episode of TDS, Andrea Cifor talks about the importance of data education to frontline employees so they can also be stakeholders of data quality.Andrea Ciforhttps://www.linkedin.com/in/andrea-cifor-081328/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
From a young age, we are taught about the differences between a need and a want. We know that we have only a few, true, basic needs, and many, many wants. In business, it’s no different, but it’s a lot harder to differentiate and understand. In this TDS episode, we’re going to explore the needs and wants that business owners have, a few pros and cons for each, as well as what the happy medium solution is.Claudio Romanihttps://www.linkedin.com/in/claudio-romani-11896380The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
There’s been so much hype around conversational AI that – unless you’re a researcher in the field – it’s difficult to know what’s possible and what’s not.Even though AI is still in its early stages of development, it can already offer many benefits to businesses. And conversational AI is surely one of them.In recent years, the need for implementing chatbots either for customer or sales support has grown tremendously, contributing to the growth of the entire conversational AI market, which is expected to be worth more than $250 million by 2027. As more businesses have started to implement conversational AI, consumers have also been getting friendlier towards chatbots in the past couple of years.But what is the state of conversational AI now?Indeed, the current pandemic has introduced some changes to every industry, and conversational AI is not an exception. And the only way we can predict where this industry will be after the pandemic is over is only by analyzing how it is changing right now.Michelle Gregoryhttps://www.linkedin.com/in/mgregory/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The COVID-19 pandemic is forcing governments and societies to turn toward digital technologies to respond to the crisis in the short term, resolve socio-economic repercussions in the mid-term and reinvent existing policies and tools in the long term. Navigating through these challenging times requires governments to adopt an open government approach and to use digital communication channels to provide reliable information on global and national COVID-19 developments. E-participation platforms can represent useful tools to engage with vulnerable groups online and to establish digital initiatives to collectively brainstorm for policy ideas to critical social and economic challenges.Effective public-private partnerships, through sharing technologies, expertise, and tools, can support governments in restarting the economy and rebuilding societies. Developing countries, in particular, will need international cooperation and support in mitigating the crisis. Therefore, regional, national, and local project-based collaborations with private sector companies, international organizations, and other stakeholders are necessary. In the long term, governments need to accelerate the implementation of innovative digital technologies such as AI-powered technology, blockchain, and drones. Investments in these technologies can tremendously support the future resilience of the health economy and public services delivery.Arya Eskamanihttps://www.linkedin.com/in/aryaeskamani/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Charles Morris, Head of Enterprise Data Science - Financial Services at Microsoft, sits down with TDS to discuss his job at Microsoft, the pandemic, and ways he has stayed connected to networks throughout the isolation period.Charles Morrishttps://www.linkedin.com/in/charleswm/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Data science comes closer to SEO every day.Data science, and more exactly artificial intelligence, isn’t new, but it has become trendy in our industry over the past few years.In this episode, we will briefly introduce the main concepts of data science through machine learning and also answer the following questions:When can data science be used in SEO?Is data science just a buzzword in the industry?How and why should it be used?Gerald Burnandhttps://www.linkedin.com/in/gburnand/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
While data science provides tools and methods to extract real value from unstructured patient information, it eventually contributes to making healthcare more efficient, accessible and personalized. The number of healthcare institutions making data-driven decisions increases slowly but steadily. At its core, data science in the healthcare industry isn’t too different from data science in other fields—the ultimate goal is to tease out meaningful and actionable insights from collected data. The healthcare sector presents data scientists with more varied opportunities than many other industries, though, from helping individual hospitals be more efficient, to influencing diagnostic and treatment processes, to mapping the spread of a pandemic. In many cases, the results of a healthcare data scientist’s work can be felt far and wide and potentially affect millions of lives.Big Data in healthcare is not unheard of. The healthcare industry is generating a significant source of data in the world. People who have skill sets in health information technology and analytics, the employment rate for them is increasing.The global pandemic has dramatically increased the need as well as the importance of data science and analytics professionals. We have seen over the months how data science professionals have come together and worked on COVID-19 healthcare data and build AI/ML models to track the outbreak and use the information for contact tracing, screening applications and vaccine development.Vamsi Chandra Kasivajjalahttps://www.linkedin.com/in/vamsichandrakasivajjala/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Today, the business value of accurate and insightful data is undeniable and only increasing in worth – but managing this data correctly comes with its challenges. As data volumes continue to grow, amplified by rapid digital transformation programs and cloud migrations in the era of mass remote working, the task of managing data becomes more costly and complex and the likes of compliance risk grow more prevalent. In this TDS episode, we looked at the reasons why it is essential to create a set of accurate, Trustworthy Data, outlining how to access and measure its value. Toma Krafthttps://www.linkedin.com/in/tomakraft/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Thomas Modern, Data Science Team Lead at Facebook, joins The Data Standard to discuss his take on analytics with empathy.Thomas LinkedIn: https://www.linkedin.com/in/thomas-modern/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
The evolution of data tools presents an opportunity for functions outside of engineering to get applications that help them make better, faster decisions. In this episode, guest Craig Utley sits down with The Data Standard to discuss the evolution of data tools.Craig Utleyhttps://www.linkedin.com/in/craigutley/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Artificial Intelligence and machine learning are conquering more and more industries and spheres of our lives, and logistics is not an exception. AI and machine learning in logistics can be a great help when it comes to the supply chain sphere. Using them, it is possible to optimize the processes, avoid mistakes that humans can make or miss, predict future opportunities and challenges. Therefore, make the business itself more successful and profitable. Here are some more details regarding the benefits of implementing AI in the supply chain.In this episode, guests Anton Bar and Judah Levine sit down with The Data Standard to discuss data in the freight industry.Anton Barhttps://www.linkedin.com/in/antonbar/ Judah Levinehttps://www.linkedin.com/in/judah-levine-79b32858/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Dweep Ashar sits down with The Data Standard to discuss long-term data processes.Dweep Asharhttps://www.linkedin.com/in/dweep-ashar/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Melih Ozbek sits down with The Data Standard to discuss his introspection during the pandemic and how his career has shifted.Melih Ozbekhttps://www.linkedin.com/in/melih-ozbek-phd-587940b0/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Joanna Palmer sits down with The Data Standard to discuss personalization in customer experience. Joanna Palmer is passionate about improving the customer and employee experience. She is a CX Client Principal at RingCentral where she partners with companies to re-imagine and improve their customer experience, ultimately driving value to their organizations. She has proven experience with many successful contact centers and digital transformations. She has over 20 years of experience focused on Customer Experience including leadership roles in both IT and Customer Service.Joanna Palmerhttps://www.linkedin.com/in/joanna-palmer-aa48601/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
This podcast – a hallway style conversation between The Data Standard and Ganesh Harinath - explores how to lead teams with empathy, what it would be like to go to space, and advice Harinath would give to young people in STEM.Ganesh Harinathhttps://www.linkedin.com/in/ganeshharinath/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Data, data, data – it’s long been a buzzword in the industry, whether big data, streaming data, data analytics, data science, even AI & machine learning — but data alone is not enough: it takes an entire system of tools and technology to extract value from data.A multibillion-dollar industry has emerged around data tools and technologies. And with so much excitement and innovation in the space: how exactly do all these tools fit together?This podcast – a hallway style conversation between The Data Standard and Alejandro Blacut from Millicom(Tigo) – explores the evolution of data architectures, including some quick history, where they’re going, and a surprising use case for streaming data, as well as Alejandro’s take on how he’d architect the picks and shovels that handle data end-to-end today.Alejandro Blacuthttps://www.linkedin.com/in/alejandro-blacut-8632a847The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Niels Hanson sits down with The Data Standard to discuss how he has adjusted to remote working as well as his journey with trying to figure out ERP systems.Niels Hansonhttps://www.linkedin.com/in/niels-hanson-46ab1117/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Wesly Clark sits down with The Data Standard to discuss how his company, J.B. Hunt, has been developing and releasing new products during the pandemic.Wesly Clarkhttps://www.linkedin.com/in/wesly-clark/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Data science is becoming a reality for change management, and although it may not have arrived yet, it is time for organizations to get ready. The companies best positioned to change in the next decade will be the ones that set themselves up well now, by collecting the right kind of data and investing in their analytics capacity. In this episode, guest Tom Fletcher sits down with The Data Standard to discuss the importance of change management in the data sector.Tom Fletcherhttps://www.linkedin.com/in/thomas-fletcher-668a934The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Over the past few years, Data Science and Analytics have become popularized and more and more ingrained in every aspect of our lives. Data science has spread to almost every industry, but there are still a few where it has just hit the surface, one of which is the gaming industry and the impact of it is growing very fast. Human-oriented games are now evolved into data-oriented games.The gaming industry is on its rise nowadays. With more than 2 billion players all over the world gaming industry is a resource of enormous revenues and these revenues are expected to grow further on. With a growing number of users, the amount of data to proceed is enlarging. Users’ playing time, interaction time, quitting point, peaks of activity, results, scores, etc. present vast material for analytics.The gaming industry has been growing exponentially. The number of active users tends to increase every minute and so does the overall income of the companies developing games. The inner infrastructure of the games gets even more complex providing more opportunities for players. An entirely new world and realities are created for the users. Top level visualization and design techniques, the latest visual effects, graphic elements and augmented reality effects provide customers with a high level of satisfaction.Data science has entered various industries and improved the principles of their functioning forever. It has brought various businesses to a qualitatively new level of their development. The industry of gaming is no exception here. Moreover, data science techniques and methodologies have become integral parts of games development, design, operation, and many other stages of their functioning.Jeremy Cloverhttps://www.linkedin.com/in/jeremyclover/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
This week we talk with Scott Taylor, also known as “The Data Whisperer.” Scott is a globally recognized thought leader and a consultant on the strategic value of proper data management. As Principal of MetaMeta Consulting, he provides Data Evangelism-as-a-Service to help enterprises and tech brands tell their data story by focusing on the WHY of business alignment rather than the HOW of technical implementation. He lives in Bridgeport, CT where he often kayaks in Black Rock harbor. He can also juggle pins and blow a square bubble.We discuss how data storytelling is important to gain funding for initiatives, and why the data management community struggles to get the message across to the business. He shares some wisdom about how to craft effective stories, and even why he uses puppets on his YouTube channel.Scott Taylorhttps://www.linkedin.com/in/scottmztaylor/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Mark Palmer sits down with The Data Standard to discuss being a parent, working as a mentor, and what he considers "big" in the data field. Mark Palmerhttps://www.linkedin.com/in/mrkwpalmer/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
With competitiveness being rated now on a global scale and competition rising up from almost any part of the world, the need for intelligence data is fast becoming a necessity to keep up with consumer and market trends. While business intelligence data concentrates on the inner workings of an enterprise—whether their metrics are within industry standards, are their processes ISO-compliant, and more—market intelligence data is sourced from external factors. As the name implies, it is gathered from the consumer markets themselves. This includes very important data points such as consumer trends, age-group-to-spending-power ratios, as well as marketing penetration in the different sections of the economic spectrum.Or Nurihttps://www.linkedin.com/in/or-nuri/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Marketing analytics is reshaping marketing forever. In today's data-driven culture it is critical to manage your marketing analytics and the marketing technology ecosystem. In this episode, guest Tom Lehman sits down with The Data Standard to discuss Tom's journey and the grand topic of marketing analytics.Tom Lehmanhttps://www.linkedin.com/in/tom-lehman/Gideon Rubinhttps://www.linkedin.com/in/gideonrubin/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
When a company promises and delivers on quality, there is a good chance that customer satisfaction and retention will be high. But paving the road to success depends on companies being well-informed about their own business. They achieve that knowledge by developing and utilizing effective metrics.Metrics are used to drive improvements and help businesses focus their people and resources on what’s important. The range of metrics that companies can employ vary from those that are mandatory – for legal, safety, or contractual purposes – to those that track increases in efficiency, reductions in complaints, greater profits, and better savings. Overall, metrics should reflect and support the various strategies for all aspects of the organization, including finance, marketing, competition, standards, or customer requirements and expectations. Metrics indicate the priorities of the company and provide a window on performance, ethos, and ambition.In this episode, guest Joel Raedeke sits down with The Data Standard to discuss his pandemic experience as well as the use of metrics in organizations.Joel Raedekehttps://www.linkedin.com/in/joel-raedeke-3b73117/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest William Denslow sits down with The Data Standard to discuss entrepreneurship in the real estate industry. During Will's senior year at Boston University, he skipped class to work on a brokerage firm that used algorithms to source deals, selling $5 million in real estate total. Hyped by that success and having identified inefficiencies in the homebuying process, Brian Zitin and Will Denslow founded Reggora to automate real estate appraisal.William Denslowhttps://www.linkedin.com/in/willdenslow/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Dr. Rodney Sappington is an entrepreneur, clinical data scientist, and researcher based in San Francisco, California. He is focused on building world-class machine learning products, improving clinical outcomes, and growing companies at scale. He is a very well-known speaker both nationally and internationally. In this episode, guest Rodney Sappington sits down with The Data Standard to discuss the work he is doing in nanotechnology.Rodney Sappingtonhttps://www.linkedin.com/in/rodney-sappington-ph-d-97ab235/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Sol Girouard sits down with The Data Standard to discuss how Girouard made it through 2020, what she has been working on, and the topic of information asymmetries.Sol Girouardhttps://www.linkedin.com/in/sreynagberman/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Gavin Wu sits down with The Data Standard to discuss what he has been up to throughout the pandemic and how he has been mindful of his team.Gavin Wuhttps://www.linkedin.com/in/junqingwu/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Andy Gray sits down with The Data Standard to discuss automation tools.Andy Grayhttps://www.linkedin.com/in/andy-gray-67b4492/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Hannes Felsburg talks about his 2020, what his company is doing right now, and how they are trying to enable an easy customer experience while participating in the stock market.Hannes Felsberghttps://www.linkedin.com/in/hannes-felsberg/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Jason Thomas, RCB Data Analytics - Mission and Decision Analytics Lead at Naval Air Warfare Center Aircraft Division (NAWCAD), joins The Data Standard to discuss data governance in the goverment space.Jason Thomashttps://www.linkedin.com/in/jason-thomas-csep-bb05388/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In today’s, episode I speak to Alisha Arora, a young woman, who is on a mission to leverage exponential technology to solve some of the world’s largest problems. Alisha is an advocate and activator for mental health, and is currently researching at MIT’s AI lab to diagnose and prevent suicide with machine learning. Alisha represents the future of STEM and so today in this inspiring episode Alisha will share her work, ambitions, and experiences working in STEM. Connect with Laura and Alisha on LinkedInLaura Edell - https://www.linkedin.com/in/lauraerinedell/Alisha Arora - https://www.linkedin.com/in/alishaarora56/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, guest Andrew Eichenbaum sits down with The Data Standard to discuss his pandemic lifestyle and how his company is going to change its staffing procedures after the pandemic.Andrew Eichenbaumhttps://www.linkedin.com/in/andreweichenbaum/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Will the United States, the largest economy in the world, enact national privacy and data protection and data governance legislation? Or will privacy regulation be left to the 50 states and other countries. The borderless nature of the Internet seems to call for uniform legislation, but enactment is uncertain.All organizations need to plan how they use data so that it’s handled consistently throughout the business, to support business outcomes.This means that organizations who successfully do this consider the who – what – how – when – where and why of data to not only ensure security and compliance but to extract value from all the information collected and stored across the business – improving business performance.It’s all about how you handle the data collected within your business.Defining an effective data governance strategy can be a major obstacle for many organizations. In today’s episode, we examine the primary challenges of data governance and delve into common misconceptions about the process. Then, we explore why proactively implementing a data governance tool is so essential to your organization.Mahesh Nairhttps://www.linkedin.com/in/mahesh-nair-2b33634/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Terrence Head sits down with The Data Standard to discuss the post-pandemic data industry challenges.Terrence Headhttps://www.linkedin.com/in/terrencerhead/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Artificial intelligence | The next frontier for investment management firms12AI unquestionably presents compelling opportunities for investment management firms, from exponential improvements to business-as-usual processes to the radical reshaping of business models. Investment management firms can start to unlock the transformative benefits of AI by implementing incremental changes to their operating model. Firms will however need to carefully manage and monitor talent and converging technologies.With traditional sources of differentiation in investment management becoming increasingly commoditized, AI is providing new opportunities which extend far beyond cost reduction and efficient operations. Many investment management firms have taken note and are actively testing the waters, applying cognitive technologies and AI to various business functions across the industry value chain. Jatin Dewanwalahttps://www.linkedin.com/in/jatindewanwala/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Forter has been very forward thinking with their use of AI, in particular around pattern and fraud detection. In this episode of the AI Today podcast we interview Iftah Gideoni who is CTO at Forter. He shares with us how machine learning can be applied successfully to detect and catch fraud, how AI and machine learning are being used for the overall customer experience at Forter, and some surprising insights about AI adoption.Iftah Gideonihttps://www.linkedin.com/in/iftah-gideoni-0b41314/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
An organization with a firm data culture makes decisions based on facts instead of gut instinct, but more importantly than that, they set a standard across the organization for how decisions are made. It’s a cultural shift away from the highest paid person’s opinion mattering the most to data driving the decision making. It’s empowering at every level and is marked by more competent teams and better business choices.Growing a data culture is an organic process that can take different forms and adopts various supporting processes. Dobrica Cosichttps://www.linkedin.com/in/cosicdobrica/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest John Gillooly sits down with The Data Standard discusses tips, tools, tactics, and tricks that are designed to help you take your productivity, time management, goals, lists, habits, and workflow to new heights. If you're looking to focus your efforts on getting the right things done and start living the good life, then this episode is for you.John Gilloolyhttps://www.linkedin.com/in/jrgillooly/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Sam Garfield sits down with The Data Standard to discuss his journey through the pandemic as well as advice he would give to young professionals in the data field.Sam Garfieldhttps://www.linkedin.com/in/samgarfield1/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Dr. Cody Allen currently works in the InSight Analytics group of Solar Turbines. Cody does research in remote machinery health management as well as optimal control through applications of control theory, fluid mechanics, and optimization theory.Cody Allenhttps://www.linkedin.com/in/cody-allen-ph-d-89691013/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
To either a model-driven company or a company catching up with the rapid adoption of AI in the industry, machine learning model interpretation has become a key factor that helps to make decisions towards promoting models into business. This is not an easy task — imagine trying to explain a mathematical theory to your parents. Yet business owners should always be curious about these models, and some questions easily raise:How do machine learning models work?How reliable are the predictions made from these models?How carefully do we have to monitor these models?David Moskowitzhttps://www.linkedin.com/in/moskowitzdavid/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Due to the recent growth and advancement in modern technology, data-driven decision-making has become a crucial part and parcel of most businesses. Data-driven decision-making entails making decisions that are backed up by hard data rather than making decisions that are only based on observation. It is applied in various fields such as health care or medicine, the manufacturing industries, and the transportation industry. The process of data-driven decision-making is also known as data-based decision management. The idea of data-driven decision making that every decision regarding data should be generalized from the main information sets that show their effectiveness and performance. Venkat Krishnamoorthyhttps://www.linkedin.com/in/venkatkrish123/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Neelam Mohanty offers an introduction to the kinds of benefits that come with integrating artificial intelligence and machine learning into your enterprise search solutions.Neelam Mohantyhttps://www.linkedin.com/in/neelammohanty/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Empathy is a right-brain activity, the kind that many people consider a touchy-feely discipline—a soft skill, as it’s called these days. But at its core, empathy is a valued currency. Sometimes leaders need to get out of their own shoes and put on someone else’s to truly understand what is happening around them.Cultivating empathy as a leadership skill allows you to create bonds of trust. It gives you insight into what others are feeling and thinking, and it helps you understand their reactions. At its foundation, empathy informs your decision-making by sharpening your perceptions and intuition.Chris Hutchinshttps://www.linkedin.com/in/cjhutchins/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Jared Praniewicz sits down with The Data Standard to discuss what his exciting realization has been from working remotely as well as how he thinks work life is going to look like as people start going back to in-person work environments.Jared Praniewiczhttps://www.linkedin.com/in/jared-praniewicz-aa1a667/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Rob Mangel sits down with The Data Standard to discuss what his COVID-19 quarantine routine was as well as how he got leadership at his company comfortable with data sources.Rob Mangelhttps://www.linkedin.com/in/robertmangelThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
At the beginning of 2020, 0.1% of all medical visits each week were conducted via telemedicine. By late April, the height of COVID-19's first wave in the US, that number had increased to nearly 14%. In this episode focusing on health and wellness tech, we're joined by Rico Urbani, Director of Enterprise Architecture and Data Solutions at Community Health Choice, to discuss advancements in telehealth brought on by the pandemic and how he spent his time during the pandemic.Rico Urbanihttps://www.linkedin.com/in/ricourbaniThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, Dushyanth Sekhar talks about the misconceptions around data science, machine learning, and AI, detailing why people misunderstand these innovations and why we should get on board with them. He divulges what trends and technologies he’s most excited about and his candid thoughts on whether or not AI will replace people’s jobs. Are you curious about opening your mind to the future of machine learning or even becoming a data scientist? This episode is for you!Dushyanth Sekharhttps://www.linkedin.com/in/dushyanth-sekhar-6603105/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
This episode features an interview with Sireesha Pulipati, Google Cloud Data Specialist at Google. In this episode, Sireesha talks about the agility the cloud provides, how data can help personalize customers’ experiences, and much more.Sireesha Pulipatihttps://www.linkedin.com/in/sireesha-pulipati/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Trust matters when it comes to relationships. Therefore, it matters when it comes to the customer experience.People line up at the Apple Store’s Genius Bar in part because they’ve come to trust that they will get a great customer experience.Whether you’re a B2B or B2C, how can you build trust with your customers?To find the answers, we connected with Sandeep Kharidhi, General Manager, Data and Analytics Platforms at Deluxe.For a constructive conversation packed with practical advice for building trust and relationships, enjoy this episode.Sandeep Kharidhihttps://www.linkedin.com/in/sandeepkharidhi/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Michael Olsen, Director - IT Division at All Native Group, joins The Data Standard to discuss the evolution of data collection.Michael Olsenhttps://www.linkedin.com/in/olsenmf/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Most organizations, enabled by massive increase in the amount and variety of data, are already using data science to understand their business performance and make operational decisions. Some organizations are just getting started with data science, while others have made significant investments and have data science teams spread across global business units. The challenge remains, regardless of your organization's maturity, how to best structure and manage data science teams so they can scale to meet the growing demands of your organization.This podcast is about what George learned about the process of building up and managing a data science team.George Bezerrahttps://www.linkedin.com/in/george-bezerra/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Process makes perfect! Or more to the point, process mining can pave the way to near-perfect business architectures, and that’s the actual stuff of digital transformation. So, what is process mining and why should you care?Ashwin Pingali, Founder/Managing Principal at Apps Consultants, joins The Data Standard to tells us about his journey as an engineer with an entrepreneurial bent and the cool thing he is working on right now and discusses process mining.Ashwin Pingalihttps://www.linkedin.com/in/ashwin-pingali/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In a suddenly volatile economy, spurred by the coronavirus pandemic, and despite government interventions, bankruptcies and increased defaults will more than likely increase. With new and immature data, produced by this unexpected economic downturn, automated modeling processes will help enhance efficiencies, but data issues will require human judgment for model development. Join Natchie Subramaniam Thiagarajah, Senior Economist/Assc.Director - Credit Analytics at Moody's Analytics to take a look at strategic approaches to calculating Credit Risk.Natchie Subramaniam Thiagarajahhttps://www.linkedin.com/in/subramaniamt/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Data Engineering is an interdisciplinary profession requiring a mix of technical and business knowledge to have the most impact. Starting a career in data engineering, it is not always clear what is necessary to be successful. Some people believe that there is a need to learn particular technologies (e.g., Big data); others believe it is a high degree of software engineering expertise; others believe it is focusing on business.There are five main tips this podcast would give to data engineers starting their careers:Learn fastDon’t succumb to the technology hypeData Engineering is not all about coding or technology or dataCoding is still an important part of the jobKnow your data and where it is coming fromMohan Ganesanhttps://www.linkedin.com/in/mohan-ganesan-a43491a3The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
What began as hoping for positive outcomes in the past has now evolved into driving better results through data and experimentation.As many product managers have found, however, designing with the customer in mind, while necessary, is not enough to ensure a positive outcome. To increase the odds of a successful product, product managers need data.We believe that companies can leverage data-driven product strategies that lead to differentiation and competitive advantage. To do this organizations must be able to pivot quickly based on their data experiments.Zachery Reichenbach-Carrhttps://www.linkedin.com/in/zackerycarrThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Dario Del Giudice, Sr Data Scientist, joins The Data Standard to discuss common myths between academic research and corporate data science.Dario Del Giudicehttps://www.linkedin.com/mwlite/in/dario-del-giudiceThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Derek Murawsky sits down with The Data Standard to discuss his career journey as well as how he has designed and lived the life he wanted to live. Derek Murawskyhttps://www.linkedin.com/in/derekmurawsky/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The world is changing and privacy is becoming a huge concern. The area of machine learning on encrypted data is booming and expected to grow significantly over the next 5 years. In this episode of the Data Standard Audio Experience, we spoke with Alexander Fried, Director of Data and Computational Science at Flybits. In a recent talk, we described the importance of data, various methods for estimating the value of data, and emerging tools for incentivizing data sharing across organizations. As we noted, the main motivation for improving data liquidity is the growing importance of machine learning. We’re all familiar with the importance of data security and privacy, but probably not as many people are aware of the emerging set of tools at the intersection of machine learning and security.Alexander Friedhttps://www.linkedin.com/in/alexander-fried-80a06542/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Advisors constantly juggle between meeting the short-term demands of their businesses while working towards their longer-term goals. To complicate things further, short- and long-term views are frequently not aligned at a particular moment in time—creating a greater lack of clarity and frustration.While it’s important for all advisors to check-in with themselves regularly to assess the balance between the two, it’s even more important for those considering a move. While the “perfect opportunity” would solve for all goals equally, it’s unrealistic to expect that perfection actually exists in one single option.So how do you find the right opportunity when your goals are seemingly at odds? You start by breaking each down, identifying both short- and long-term needs and goals, and ranking them by importance.Chris Murphyhttps://www.linkedin.com/in/chris-w-murphy/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Following a data-driven approach is the best way of running a successful business. Data collection and analysis applies to many different areas- from understanding customer trends to reducing operational costs. But data also applies to risk management. By using analytics to assess business risk, you can develop more secure systems that protect against cyber-attacks.Risk assessment is a critical part of implementing a data security plan. However, many companies assess risk by merely referring to previous experiences or industry trends. This approach is less specific and may result in higher costs, non-compliance with established regulations, and vulnerability to potential data breaches.Luckily, following a data-driven approach will help your business protect customer data and assess the effectiveness of current controls. Risk assessment via data analytics will also result in the implementation of better risk management strategies.Prasanna Madabushihttps://www.linkedin.com/in/pmadabushi/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode of the Data Standard Audio Experience podcast, we discuss with Netrality Data Centers, the evolution of the edge and how the deployment pace has accelerated. We also dive into the strategies that will support growth in the months and years to come. Craig Waldrop, VP of Channel & Strategic Alliances at Netrality Data Centers, joins The Data Standard to discuss how his industry and company use data to drive their businesses.Craig Waldrophttps://www.linkedin.com/in/craig-waldrop-416586/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Users of large online dating sites are confronted with vast numbers of candidates to browse through and communicate with. To help them in their endeavor and to cope with information overload, recommender systems can be utilized. Given the massive user bases of these dating sites, there is a need and value in helping users combat information overload by filtering the most relevant partner candidates of the abundant pool of choices. Otherwise, users have a hard time finding a partner, as they have to browse through and communicate with potentially hundreds, if not even thousands, of users and profiles. While important attributes such as age, location, gender, and relationship preference can be used to cut down on the number of viable candidates, the leftover set may still be huge especially for users living in densely populated areas. Recommender systems are a means to combat this information overload and provide users with candidate recommendations personalized to their preference and profile. Moreover, there is value in such recommender systems, even for smaller dating sites, because users’ attention and time can be devoted to only a handful of choices at a time and poor matches may lead to repeated rejections and discouragement. Recommender systems may also be used to reduce the burden of popular users, who may receive unruly amounts of messages, and relieve the anguish of unpopular users and users who continually get rejected by balancing the way users occur in recommendations.Dinh Thi Buihttps://www.linkedin.com/in/dinh-thi-bui/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
On this week’s episode of the Data Standard Audio Experience, we talk with Chris Bergh, the CEO and head chef at Data Kitchen. DataKitchen’s mission is to provide the software, service, and knowledge that makes it possible for every data and analytics team to realize their full potential with DataOps.Highlights from this week’s episode include:Chris’ background and how the lessons learned in the Peace Corps and at NASA apply to him todayWhy AI left Chris feeling like a jilted loverMost projects that people do in data analytics failThree things that DataOps focuses onComparing and contrasting DevOps and DataOpsThe types of data that DataKitchen handles and building a product or a service around DataOpsFixing problems at the source instead of just offering a tool to slightly improve things downstreamWhere we are at in the process of how companies are going to run on dataChris Berghhttps://www.linkedin.com/in/chrisbergh/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
As the world consumes more and more data, businesses increasingly require experts who know how to handle large amounts of customer information, competitor research and product performance results. They also need professional developers to build and manage their increasingly complex websites and apps. These two distinct needs have led to two exciting tech fields: data engineering and software engineering. The two sometimes overlap, but actually have different areas of expertise.To those outside the tech world, terms like “data engineer” and “software engineer” may sound interchangeable, since both rely heavily on programming skills. Some may even assume that data engineers and software engineers do the same thing.In reality, software engineers usually only engage in data infrastructure to a limited extent. Their primary focus is on building websites that function well for the end-user. The task of data engineers, however, is to maintain large datasets and build the structures that house them. So while each profession involves a common background of data management, software engineers and data engineers have vastly different responsibilities.In short, data engineers examine the practical applications of data collection and help in the process of analysis. Data engineers work closely with large datasets, and build the structures that house that data long-term. Data engineers should be well versed in programming languages like SQL that allow them to build, maintain and secure big data. Most data engineers have been software engineers at some time in their career and have moved on to specializing in data engineering.Software engineers are also skilled in computer programming, but they perform work that includes designing and developing operating systems, as well as front and back-end development. While some software engineers rely heavily on data, you’re not guaranteed to focus on data analysis if you pursue a career in engineering. Engineers who focus on front-end web development, for example, are much more concerned with the look and feel of a website, rather than organizing the data on the back end.Daniel Peckhttps://www.linkedin.com/in/peck/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Everybody comes into Data Science from a different background. Some studied maths, some took stats classes, some came from finance, etc.Ruben's story is especially unique in that way – for many years he used to be a Chemical Engineer!What prompted him to make the transition? His MBA. Yes! Ruben found a way to structure his MBA in a way that leads him to an ultra-successful career in Data. And he hasn't looked back since.We talked about how his company has transformed throughout the pandemic, how to set up and promote self-serve analytics systems, how to keep your workflow under control, and the importance of mentors in Data Science.Ruben Kogelhttps://www.linkedin.com/in/rkogelThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Information as an asset is still in the “early adoption” phase, which makes it a competitive differentiator for leading organizations as they focus on digital transformation. In turn, data and analytics become strategic priorities.Data and analytics are the key accelerants of an organization’s digitization and transformation efforts. The phenomenon of Big Data has changed the business world like never before. The most important part of this transformation is the strong emergence of analytics to support the shift in modern enterprises from a process-centric viewpoint to one that is more data-centric and data-driven. The data that surrounds the enterprise is being harnessed into information that informs, supports, and drives decision-making in a timely, repeatable manner.Sudeep Krishnanhttps://www.linkedin.com/in/sudeepkrishnan/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Austin Lee sits down with The Data Standard to discuss how he found a rhythm for his work life and personal routine throughout the pandemic.Austin Leehttps://www.linkedin.com/in/austinrlee/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Sometimes having a seat at the table in the workplace isn’t enough. Today’s guest reflects on her career trajectory and what’s helped her to find her voice, build confidence, and overcome nagging feelings of self-doubt, including great bosses, professional coaching, setting expectations, and running marathons.Ashley Odomhttps://www.linkedin.com/in/ashleymodom/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Rapid technological advances in digitization and data and analytics have been reshaping the business landscape, supercharging performance, and enabling the emergence of new business innovations and new forms of competition. At the same time, the technology itself continues to evolve, bringing new waves of advances in robotics, analytics, and artificial intelligence (AI), and especially machine learning. Together they amount to a step change in technical capabilities that could have profound implications for business, for the economy, and more broadly, for society.Blake Treuhttps://www.linkedin.com/in/blake-treu/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The past few months certainly haven’t been easy for small businesses. Many had to shut their doors due to the coronavirus pandemic. While some may never reopen, others are ramping up their business — and hoping they don’t have to shut down again. This podcast will focus on small businesses and what we can do during the corona virus crisis. It will focus on what to do if we can’t get aid right away, the mindset you should have as a small business towards marketing, management, sales, and more.Alka Guptahttps://www.linkedin.com/in/alkaakgupta/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Coping with quarantine due to the coronavirus, the new-to humans virus that causes respiratory infection and can lead to serious or fatal health complications has been challenging for just about everyone. In the midst of a global pandemic, it’s hard to figure out ways to deal with the new lifestyle of sheltering in place or going out to do essential work. We cover everything about data and affordable housing to make you a smarter, more successful data-driven pro. Even if you’re new and data curious, you’re going to love it!Ty Tuckerhttps://www.linkedin.com/in/tyhtucker/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Today, we speak with OKCoin’s Bob Lehto, the International Head of People at the company.OKCoin is on a mission to make crypto investing and trading more accessible to anyone around the world. Founded in 2013, OKCoin is a global exchange numbering 250 employees with its headquarters offices in San Francisco, and local offices in Malta, Hong Kong, Singapore, and Japan. The company is a collective of global citizens with a common passion to help decentralize finance and level the economic playing field for everyone around the world.Bob Lehtohttps://www.linkedin.com/in/boblehto/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Although the term “data scientist” has a nebulous definition at best, there are a few characteristics that seem to unite us: we are curious, we like finding nuggets of information buried within a mass of data, we like solving hard problems, we are technically inclined. There are tons of fantastic programs offering master’s degrees in data science and analytics, and these programs teach statistics, data mining, machine learning. But what if you need to build an actual product that is used by people? Does knowing the mathematics of back propagation help you?To our knowledge, most data scientists are not trained in product development. Yet, products that are underpinned by machine learning are becoming essential tools for many businesses, particularly in the retail and eCommerce space. Building data products requires data scientists, but as a whole, we are…not really great at building them. How can we contribute our talents to this process without derailing it and making our product development leadership roll their eyes and cringe?David Herberichhttps://www.linkedin.com/mwlite/in/david-herberich-62685618The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The COVID-19 pandemic has been raging for several months now and will likely continue for months to come. Amid this ongoing crisis, people need resources to stay as safe as they can for as long as they can. Data science and its related technologies are enabling such actions, playing an essential role in global safety.Times of hardship often serve as proving grounds for systems that people have boasted about in calmer days. The COVID-19 pandemic is no exception, and data science has more than proved its value. Data, and more importantly, the way people use it, is shaping and refining approaches to COVID-19 safety.Gavin Smarthttps://www.linkedin.com/in/gavin-smart-8687a485/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Everyone is suddenly a remote worker. In the wake of COVID-19, many employers are sending staff home as the coronavirus spreads around the globe, while others are forced to stay at home under quarantine.Are you prepared? How will you cope? You may even be secretly excited by the prospect. Either way, you need a plan.Kish Khemanihttps://www.linkedin.com/in/kishkhemani/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Out of the three billion pairs of DNA molecules that make up the human genome, only 0.1% are unique to each person. To find patterns useful to medical research in such a vast sea of data, researchers can benefit from tools that cut through the noise. Fortunately, these are the same problems that big data has been trying to solve for almost a decade. Biotechnology, broadly encompassing technological applications using biological systems, finds itself in similar conditions to those that allowed big data to emerge. As the volume and variety of medical data grow, it becomes more advantageous to refine it into information that can be used to make decisions. Because of the vast quantity of patient data now readily available, ML has now become a valuable tool to model the behavior of drugs and find potential applications for existing and new molecules. Big data is not just in the future of the pharmaceutical industry, it is shaping its present.Data science and AI have a growing role in drug discovery and development. We speak with a leader in data science for health care, Neal Zundell, to learn more.Neal Zundellhttps://www.linkedin.com/in/nealzundellThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Artificial intelligence and machine learning (AI/ML) have spectacular potential to provide transformational insights. However, it’s often difficult to scale AI/ML models to the enterprise. In this episode, Nandan Thor, discusses the emerging discipline of AI modeling.Nandan Thorhttps://www.linkedin.com/in/nandan-thor-205374128/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Companies can put their information to work by teasing out novel patterns, driving productivity, and creating new solutions. In an increasingly customer-centric world, the ability to capture and use customer insights to shape products, solutions, and the buying experience as a whole is critically important. Research tells us that organizations that leverage customer behavioral insights outperform peers by 85 percent in sales growth and more than 25 percent in gross margin. Customer data must be seen as strategic.Amit Mudgalhttps://www.linkedin.com/in/amitkmudgal/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Jeremy Ernst sits down with The Data Standard to discuss how to upscale your data science problems. Jeremy Ernsthttps://www.linkedin.com/in/ernstjeremy/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The first step of data-driven business transformation journey is looking at changing the way organisations think about innovation and growth, and the key to success is data that that is accurate, relevant, and timely. Data quality and data governance are critical to achieve the data-driven business transformation that companies are looking for. Technological advances and new ways of working are changing the way we look at data governance and quality in the context of rapid business change. Whether you are a Chief Data Officer looking to understand what new technologies and methodologies are available or a businessperson trying to understand the challenges around data quality, listen to this educational podcast to discover how data quality and data governance can support your business transformation initiatives.Anna Swigarthttps://www.linkedin.com/in/annaswigart/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Self-driving cars: the greatest automotive industry disruption since Henry Ford’s Model-T assembly line… just around the corner. Right? That’s the hype—but is it a reality? Are we mere blocks away from our neighborhood streets and freeways being filled with autonomous cars? Find out in the premiere episode of The Data Standard in which Girish discusses AI autonomous vehicles.Girish Venkataramanihttps://www.linkedin.com/in/girish-venkataramani-8438942/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Working as a data science consultant has a lot of advantages for your career. You get to work on projects with the most successful companies in the world. You learn from the best experts around, and you have the benefits of working with large consulting firms that offer you countless opportunities to grow your career and skills. You also have to be mindful that all of these benefits come at the price of an intensive workload in a high-pressure environment. If you are ready for all of this, entering the data science consulting industry can be one of the most significant steps towards success in your career.Kim Kraunzhttps://www.linkedin.com/in/kimkraunz/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The world of biotechnology is increasingly driven by data. As the number of biotech companies continues to grow, so does this industry’s need for data scientists, data analysts, and other technologists. With demand for data—and the associated concerns of where to store it, how to process it, and how data pipelines will be structured—on the rise, there will be plenty of opportunities in biotech for those specializing in app development, software engineering, cloud architecture, and other fields.Kurt Thornhttps://www.linkedin.com/in/kurt-thorn-3704201/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Are you a Software Engineer looking to make your next career move? Are you considering making that leap into a Leadership position? Or, are you already an experienced leader wanting to transition from a Corporate to a Startup, but unsure if it’s right for you??Who better to ask than someone who has made these exact career moves with great success? Well, that’s what we did when we were lucky enough to sit down with Jeff Ptak, Director of Data Engineering, at Sunbelt Rentals. With over a decade of hands-on experience, prior to his move into leadership, Jeff brings a real-level of empathy to his team, and thought-leadership to Sunbelt Rentals. We found out exactly what Jeff thinks it takes to be a leader & VP - from the skills, to the mindset - as well as discussing how a change in industry can be a beneficial career move. We also touch on the alternative career paths that engineers can take if they think leadership might not be for them!Jeff Ptakhttps://www.linkedin.com/in/jeffptak/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this Data Standard Audio Experience episode, we focus on how data science can help advance the healthcare industry. Billions of people can benefit when a more focused integration happens. Start tuning in to know more!Data Science, Artificial Intelligence, and Machine Learning can surely provide the needed solutions for the healthcare industry. These emerging technologies have already proven their value and have defined industries like communications, banking, retail, etc.So, today, we discuss how data science can change the healthcare industry for the better. It doesn’t matter if you’re in a different sector since there will be a thing or two that you can take from this episode and apply to your career. This also broadens your horizons and serves as a good starter if you want to jump into the data science and healthcare industries.Neeta Upadhyayhttps://www.linkedin.com/in/neetasupadhyay/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Meet Juan Manuel Contreras, Ph.D., a cognitive neuroscientist turned data science manager at Uber. Juan Manuel works at the intersection of data science, law, and economics to help drive Uber’s legal and business strategies. In 2015, he was one of HuffPost’s “40 Under 40: Latinos in American Politics” and he previously worked in the White House Social and Behavioral Sciences Team during the Obama Administration.Juan Manuel Contrerashttps://www.linkedin.com/in/jmcontreras/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
What do data scientists do? Data science is about infrastructure, testing, using machine learning for decision making, and data products. Data science is being used in numerous fields, but it’s not all about deep learning or the search for artificial general intelligence. In fact, the skills needed include communication and storytelling. But data science is becoming more specialized, and with that the skills data scientists need are evolving. In addition, ethics is becoming a bigger and bigger challenge. Eric goes over his experience, sharing interview mistakes to avoid, tips on getting your foot in the door for jobs, and what it’s like to enter the data science industry full time. This is a great place to look if you’re about to graduate from your data science program.Eric Federhttps://www.linkedin.com/in/efederThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Every business aims to be data-driven, but not all of them succeed in that effort. In order to be able to truly derive insights from the data that an organization collects, there are certain foundational capabilities that they need to have the capacity for. In this episode, she shares her thoughts on the core elements that are necessary for every business to be data-driven, how she is helping companies incorporate those capabilities into their structure and the ongoing support that she is providing through a network of mastermind groups. This is a great conversation about the initial steps that every group should be thinking of as they start down the road to making data-informed decisions.Archana Ganapathihttps://www.linkedin.com/in/archanaganapathi/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
You put in the time learning the skills, you took the right approach to your job applications, and now you’ve found yourself with a job in data science. That’s great! But now that you’ve got that job, how do you keep it and excel at it? How can you prove your value as a great data scientist?That’s a question that isn’t always as easy as it sounds. Having the skills is key, but a successful data scientist also needs to know how those skills can be applied to produce a meaningful business impact — one that justifies the high salaries data scientists command.Your analysis has to be good. But more importantly, it has to bolster your company’s bottom line.At larger companies, making this happen is often pretty straightforward. A big company is likely to have an established data science process and a team that you fit into, with clearly defined goals that management knows will generate a return on their data science investment.But at smaller companies, it can be considerably more difficult. You may be the company’s first data science hire, and there may not be a clear vision for how your role will help the company succeed. You might be tasked with “finding opportunities” and left to your own devices.This kind of freedom can be a blessing, but it can also be a curse if you’re not sure where you can make an impact. And it can be really difficult to handle when it’s combined with the impostor syndrome that often comes when stepping into a new role at a new company.Don’t despair, though — you can do this!Ragini Okhandiarhttps://www.linkedin.com/in/ragini-okhandiar/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The world has dramatically changed in just a few weeks. As companies around the world shift to remote work, how do we navigate this crisis? The Data Standard talks to Mark about how we communicate with our friends, family, and coworkers during a time when Zoom and Slack are our primary tools for understanding each other.Mark Connollyhttps://www.linkedin.com/in/mconnolly1993/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The COVID-19 pandemic disrupted supply chains and brought economies around the world to a standstill. In turn, businesses need access to accurate, timely data more than ever before. As a result, the demand for data analytics is skyrocketing as businesses try to navigate an uncertain future. However, the sudden surge in demand comes with its own set of challenges.How the COVID-19 pandemic is affecting the data industry and how enterprises can prepare for the data challenges to come in 2021 and beyond.Andrew Custagehttps://www.linkedin.com/in/andrew-custage-8934381b/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Discussing almost coining Machine Ethics, Big Data and social sciences not having the answer to AI ethics, prima facie duties, and robots, everything is going to have to have some ethics and AI as the continuation of humanity into space. This month we’re chatting with Robert Moss about responsible AI, defining AI ethic terms and collaboration, where does the interest in AI ethics comes from within organizations, how is it ethical for AI is related to good business outcomes, the connection of ethics and risk, and much more.Robert Mosshttps://www.linkedin.com/in/robertlmoss/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Catherine and Roberto discussed a range of topics including:The quantitative finance landscape.The challenges in identifying and using alternative data sources.Applications of machine learning in finance, including deep learning and reinforcement learning.New natural language models and their applications in finance.Model Explainability and Model Risk Management.Artificial General Intelligence.Roberto Strepparavahttps://www.linkedin.com/in/streppa/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
We are living now in a volatile, uncertain, complex, and ambiguous world. And, to sustain and succeed as a business in this environment, a winning data and analytics strategy is key. With the enterprises becoming data companies globally, there is a clear shift in the analytics paradigms today. We want to infuse AI across the value chain, but can we truly ignore the fundamentals of data management? Garbage in is garbage out after all. How can organizations create a data and analytics strategy to future-proof their data management landscape?Austin Kronzhttps://www.linkedin.com/in/austinkronz/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Chenniappan Solaiyappan, Director of Product Management, Data and Analytics Platform, ClaimSphere at Cognizant, joins The Data Standard to discuss parenting in the modern age.Chenniappan Solaiyappanhttps://www.linkedin.com/in/chennysThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Dr. Alex Constantin is a Data Scientist and Diabetic on a mission to take the mental burden and frustration out of living with diabetes. So in this episode, she teaches us how data science can improve the lives of diabetics everywhere!Dr. Alex Constantinhttps://www.linkedin.com/in/aeconstantin/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
As the world reacts and evolves to our current market conditions—namely, massive disruption—organizations are forced to accelerate at an even greater pace. Implementing a winning data strategy has been realized as a business imperative to drive transformation through reduced costs, increased revenue, mitigated risk, and improved experience. Having a strong data strategy aligns to each of these core areas because ultimately, it’s an enabler of them.Dave Melillohttps://www.linkedin.com/in/davemelillojr/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Today, many of us spend our workdays online, in one-on-one and group meetings. Here are some tips to help you make your presence known and have a positive impact, especially during large group meetings:Be visible. Turn your camera on to simulate in-person attendance.Prepare. Know the meeting’s purpose and agenda, complete assigned prework, review relevant notes from prior discussions, and write down ideas you’ll contribute and questions you’ll ask.Use active listening skills to test your understanding of new or complex ideas – you’ll help yourself and others.Using statements like, “Robin, what are your thoughts about this approach?” is a good way to invite others to contribute.Support ideas offered by colleagues, especially those who have a hard time being heard and valued over the voices of the favored.Summarize key discussion points and action items. This is a helpful end-of-meeting strategy, and it can also be an effective way to refocus the discussion or transition to a new topic.David Coxhttps://www.linkedin.com/in/coxdavidj/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Defining an effective data governance strategy can be a major obstacle for many organizations. In today’s episode, we examine the primary challenges of data governance and delve into common misconceptions about the process. Then, we explore why proactively implementing a data governance tool is so essential to your organization. Listen to the data governance management podcast episode to get more insights.John Moranhttps://www.linkedin.com/in/johnmoran/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
How do you think about your customers? Not in business? How are businesses thinking about you? Customer Analytics is interesting because the techniques can be applied to a number of different disciplines.Alexander Cookhttps://www.linkedin.com/in/amcookamc/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Stefanie Molin wrote the technical book “Hands-On Data Analysis with Pandas”. Her work shows readers how to analyze data and get started with machine learning in Python using the powerful pandas library. She’s a software engineer and data scientist, and a member of the Security Data Science team at Bloomberg that researches and develops solutions using data and machine learning to help improve and automate Bloomberg’s information security processes. In her job, Stefanie focuses on identifying and answering security-related questions using data and developing software to solve them. She holds a bachelor’s degree in Operations Research from Columbia University’s Fu Foundation School of Engineering and Applied Science (CUSEAS), with minors in Economics, and Entrepreneurship, and Innovation.Stefanie Molinhttps://www.linkedin.com/in/stefanie-molin/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Slater Victoroff is the CTO and co-founder of indico.Indico creates meaningful process automation around business documents.We talk about What is Natural Language Processing Using A.I. to create meaning behind business documents The unique school (Olin) that Slater attended The number of textbooks Slater bought in school (answer: zero) How indico has attracted $8.4 Million by solving a massive problem Slater nominates his co-founder as a future guestA summary of Slater’s accomplishments with indico in his own point form notes while serving as CEO of indico for ~4 years.1. Founded in Olin College dorm room (literally) as a developer platform 2. Accepted to Techstars Boston; Raised ~$5M of venture capital from top-tier VCs including General Catalyst, .406 Ventures, Boston Seed, Hyperplane as well as many high-profile Boston Angel Investors 3. Led successful highly technical content marketing strategy including the earliest tutorials and reviews for tensorflow 4. Scaled backend system to handle several billion monthly API calls and a developer ecosystem of roughly 10k developers 5. Closed multiple six-figure enterprise contracts and coordinated joint press releases with customers such as interlinkOne, and Manulife.Slater Victoroffhttps://www.linkedin.com/in/slatervictoroff/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
For a long time, the music industry is in need of a facelift and the advent of big data seems to fulfill this. The musicians might be provided with a more successful revenue model with the emergence of big data. This represents one of the largest industry shifts that music has witnessed in many years. Let us take a look in this podcast with Chris about the possibilities that big data provides for the music industry.Chris Dornhttps://www.linkedin.com/in/chrisgdorn/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
The COVID-19 pandemic has impacted every industry around the globe, but perhaps few as much as the property & casualty insurance industry. From an incredible increase in claims payouts to fears that the economic slowdown will result in customer loss, the industry is struggling to overcome multiple challenges while continuing to meet the current and future needs of its customers.The insurance industry’s biggest and most valuable resource is the data that insurance companies have collected over the years on everything from weather risk to consumer behavior. Insurers had only just begun to incorporate artificial intelligence and machine learning (AI/ML) into processing this data before the pandemic erupted.Now, new pressures are making it even harder for larger insurers to keep pace, and even more difficult for midsize and smaller insurers to adopt AI/ML technologies because of long development timelines and traditionally high investment requirements. As such, many of these companies are looking for innovative new technologies to help optimize their AI/ML investments and/or launch AI/ML programs with limited resources.Connan Sniderhttps://www.linkedin.com/in/connan-snider-4249311b/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Digital transformation is the integration of digital technology into all areas of a business, fundamentally changing how you operate and deliver value to customers. It’s also a cultural change that requires organizations to continually challenge the status quo, experiment, and get comfortable with failure.Digital transformation is imperative for all businesses, from the small to the enterprise. That message comes through loud and clear from seemingly every keynote, panel discussion, article, or study related to how businesses can remain competitive and relevant as the world becomes increasingly digital. What’s not clear to many business leaders is what digital transformation means. Is it just a catchy way to say moving to the cloud? What are the specific steps we need to take? Do we need to design new jobs to help us create a framework for digital transformation, or hire a consulting service? What parts of our business strategy need to change? Is it really worth it?Afrozy Arahttps://www.linkedin.com/in/afrozy-ara-57527612/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, Prism’s Yi Li sits down with The Data Standard to discuss the best practices when presenting to stakeholders from various companies. Yi Lihttps://www.linkedin.com/in/yi-li-stats/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
With COVID-19 necessitating the rapid shift to working remotely, we felt it would be particularly relevant to share insights from a guest of ours — Sebastian Wilson — because our goal is always to help you navigate through the change we are all facing so you can create the right momentum to move forward.Sebastian preaches the tenets of process and preparation that enable leaders to boost collaboration, productivity, and morale among their teams. In this episode, we highlight his specific tips and advice for facilitating virtual meetings.When you have the right parameters in place, the transition to remote work becomes easier, and you can move faster toward achieving your initiatives.Sebastian Wilsonhttps://www.linkedin.com/in/sebastianwilson1The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Are you on a quest to become a Data Scientist? Learn from people who have been through the same difficulties and challenges you are probably facing right now!Nowadays everything we need to know is at a distance of a click. The Internet is filled with information but there are times where a full-made Data Scientist, an apprentice, or even a wannabe gets tired of searching for new themes, reading so many blogs, and viewing a great number of Youtube videos. If you fit this description or are just looking for other learning sources, this podcast is for you.Isha Goyalhttps://www.linkedin.com/in/isha-goyal02/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In these difficult times, most interviews are being conducted remotely either over the phone or by video call. So, in this podcast, we’re joined by Chris Morgan, Data Science Manager at The General®. Chris is here to share his expert advice for those who are worried about interviewing remotely, to help them overcome their fears and secure their next job.Chris Morganhttps://www.linkedin.com/in/morganchristopher/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
P B K Chaitanya, Director, Analytics, Global Analytics, and Research Center (GARC) at MetLife, joins The Data Standard to talk about research centers for data science.Chaitanya Co-build MetLife’s first large scale data and analytics capability center a.k.a Global Analytics and Research Center (GARC) - to support enterprise scale. Chaitanya oversees the research center where experts use cutting-edge analytics, informatics, and computing methodologies to conduct research and develop innovative solutions to address high-impact problems across disciplines.P B K Chaitanyahttps://www.linkedin.com/in/pbk-chaitanya/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Healthcare organizations have access to more data than ever, presenting an opportunity and a responsibility to deliver personalized care. Learn how data and analytics can unlock insights to evolve individual care plans. You will also hear about the impact of artificial intelligence, interoperability mandates, and keys to enabling operational resiliency. Kelvin Wurstenhttps://www.linkedin.com/in/kelvin-wursten-924b834/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Organizations that once stored gigabytes of data now find themselves having to manage petabytes or even exabytes across their IT infrastructures. The borderless Internet, which allows applications to reach nearly anywhere, is one reason for the unprecedented data growth. Perhaps an even bigger driver is the increasing use of the public cloud for highly accessible and cost-effective compute and storage services.To harness the value of their massive data volumes, companies are building modern, cloud-based data infrastructures that help them create a universal version of “truth.” These foundations unify siloed pockets of data for a holistic view, empowering everyone in an organization to make better-informed decisions and act with confidence.Wendi O'Neillhttps://www.linkedin.com/in/wendioneill/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Premier Inc.’s Senior Product Director, Rush Shah joins us for an extremely enlightening and forward-thinking discussion around how big data and analytics currently influence the development of medical technologies. Then shares how the utilization of these tools will influence moving towards a more connected healthcare system to better patient’s lives and the steps she imagines we need to take to build the infrastructure to support it.Rush Shahhttps://www.linkedin.com/in/rushshah/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
There’s so much information out there on how magical insights from data can take your communications (comms) to the next level. And if you’re feeling confused, bewildered, or lost by it all, don’t worry — you are not alone. This podcast simply explains what data won’t help you do clever comms, what data will help, and how you can do clever comms that are data-driven.Spencer K’Burghttps://www.linkedin.com/in/spencerkburg/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
We are living in a world in continuous evolution, all companies need to drive their activity to new forms of technology, this is why Digital Transformation becomes a means of survival. In this revolution, cloud computing has a key role, it becomes the catalyst for this transformation. Nowadays every company measures its performance through customer experience, a cloud-enabled and cloud-delivered business model supports organizations to adopt newer channels to offer high-level customer experience by differentiating its strategy and solutions over the current market competitors. The recent necessity of remote work makes the shift to the cloud more urgent than ever for enterprises. No matter where a business was in their cloud transformation before this new era began, employees need to securely access work software and data from home, now. Chris Norrishttps://www.linkedin.com/in/chrisnorris3/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Investment managers are using big data and artificial intelligence to enhance the diversification and risk/return potential of portfolios. Investment Management firms have a wealth of information and data at their fingertips. Applying big data principles to slice and parse data by region, asset type, etc., means analyzing large data sets, both structured and unstructured, to increase ROI and make proper predictions for future investments. The easy part is knowing that you already have a lot of data; the harder part is knowing how to use that data in meaningful ways. Kanwar Gaurav Paulhttps://www.linkedin.com/in/kanwargaurav/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode of the Data Standard, we invite Luiz on to the show to discuss what makes up "security data science". Luiz delves into the tools of the trade, posit on the future of the intersection of security and data science and relates his own personal & professional experiences trying to introduce "data science" into infosec.Luiz Fernando Santoshttps://www.linkedin.com/in/luizffs/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Mekki El Boushi sits down with The Data Standard to discuss how his perspective has shifted on the power of AI as well as the hurdles that he has experienced and anticipates seeing with AI.Mekki El Boushihttps://www.linkedin.com/in/mekki/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Ben Ogorek sits down with The Data Standard to discuss various ways to avoid mistakes and errors in predictive modeling.Ben Ogorekhttps://www.linkedin.com/in/benogorek/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode of the Data Standard, Anurag shares best practices for navigating uncertainty in the wake of COVID-19. Conversations focus on how teams should strategize, types of projects to pursue, and tips for working from home.Anurag Voletihttps://www.linkedin.com/in/anuragvoleti/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
From artificial intelligence to small data and graph technology, data and analytics leaders should think about leveraging data industry trends. When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on “big” data to a class of analytics that requires less, or “small” and more varied.Each of the trends fit under one of these three main themes:Accelerating change in data and analytics: Leveraging innovations in AI, improved composability, and more agile and efficient integration of more diverse data sources.Operationalizing business value through more effective XOps: Enables better decision making and turning data and analytics into an integral part of businessDistributed everything: Requires the flexible relating of data and insights to empower an even wider audience of people and objects.Paul Dorasilhttps://www.linkedin.com/in/paulrdorasil/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Adriano Ruz sits down with The Data Standard to discuss how COVID-19 has affected work life, tips for getting through these stressful times, and different ways to run remote meetings.Adriano Ruzhttps://www.linkedin.com/in/adriano-ruz-0a231316/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
What is AI? Why care about AI ethics? What are problems arising from AI being introduced into our contemporary society? Benjamin Perryman joins The Data Standard to explore current ethical challenges arising with the increasing adoption of AI in everyday life.Benjamin Perrymanhttps://www.linkedin.com/in/benjamin-a-perryman-phd/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Justin Conley joins The Data Standard for a deep dive into causal inference and how it can help businesses understand causes and impacts for better decision making. Referring to current events as examples, Justin explores how we interact with, analyze, trust, and interpret data - addressing underlying assumptions, counterfactual frameworks. Stay tuned to learn more about causal inference and the insights you can unlock with it.Justin Conleyhttps://www.linkedin.com/in/justinco/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
You must have read many times that ‘Data is the New Oil’. In today’s fast-paced digitally driven world, data is truly ‘fueling’ the growth of businesses and economies worldwide through intelligent analytics. However, what most of us forget is the fact that just like oil, data has to be refined to give accurate, measurable, trustworthy & reliable outcomes. Apart from losing faith in customers, dealing with an enterprise-wide poor data quality & security can also be very cost-intensive. Moreover, while handling data, non-compliance to stringent data privacy & security laws like GDPR – EU, CCPA – California, US and The Personal Data Protection Bill – India (proposed) may also attract heavy penalties and fines. Hence, the quality, privacy, and security of data are three factors that are of prime importance, thankfully, they can be achieved and maintained through various data governance programs. So, if you are keen on improving data quality & data privacy for your enterprise or learning more about it, do not miss this Data Standard Audio Experience with Bobbi Caggianelli.Bobbi Cagianellihttps://www.linkedin.com/in/bobbi-caggianelli-07058428/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Alon Rozental sits down with The Data Standard to discuss real-life constraints with TV media.Alon RozentalDirector of Data Science at Amobeehttps://www.linkedin.com/in/alon-rozental-893a9950/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, our guest AB Guandala sits down with The Data Standard to discuss how data drives the business model in the healthcare industry.AB GundalaChief Data Officer at SickleSoft Inc. https://www.linkedin.com/in/ab-gundala/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
Learn how agile disciplines are applied to the complexities of data science to demonstrate incremental value within intelligent systems and solutions. Join The Data Standard Audio, as we interview Director of Data Products Jackie Zuker. The result is a better understanding of how agile practices are adapted to the uncertainty of machine learning, and how data scientists fit within a cross-functional agile development team.Jackie LinkedIn: https://www.linkedin.com/in/jackiezuker/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
In this episode, guest Rukmani Gopalan sits down with the Data Standard to discuss big data solutions using Azure. Rukmani LinkedIn: https://www.linkedin.com/in/rukmanigThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Getting it right or as close to right as possible is critical when collecting data. The consequences of failing to properly collect data include the inability to answer your research questions, inability to validate the results, distorted findings, wasted resources, misleading recommendations and decisions, and harm to participants. There are many things that could go wrong when collecting data, which may ultimately compromise the trustworthiness of your findings. To help you think through potential challenges and how to address them, listen to The Data Standard Audio Experience with Kevin Imboden.Kevin LinkedIn: https://www.linkedin.com/in/kevin-imboden-5172353/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/
With the growing demand for developers, the IT industry is tasked with bringing more workers into the field. Stereotypes and ignorance are a major blocker to this initiative. Annie speaks about her journey into technology (from a background in film and art) by learning the InSpec framework, and how she attained the skills necessary to become a cloud automation engineer. Annie’s aim is always to make the right thing to do the easy thing to do.About our host:Laura Edell Chief Data Scientist, AI Markets & Innovation @ Microsoft https://www.linkedin.com/in/lauraerinedell/About our guest: Annie HedgpethTest Infrastructure Engineer at HashiCorp https://www.linkedin.com/in/annie-hedgpeth/The Data Standardhttps://www.linkedin.com/company/the-data-standard/https://datastandard.io/
This Data Standard podcast is simply all about electric and autonomous vehicle technology and the EV and CAV industries. Whether it’s an episode with special expert guests to learn more about their niche in the industry or going into in-depth explanations on how various EV and autonomous technology works, you are sure to learn a lot.Michael LinkedIn: https://www.linkedin.com/in/kimpute/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/For more information about The Data Standard visit https://datastandard.io/
In this episode of the Data Standard, we’re joined by Kimberly – data journalist at a large healthcare company in Buffalo, New York, and is also the founder of Buffalo Business Intelligence. Buffalo Business Intelligence is a free word-of-mouth networking group designed to unite users using various data visualization tools. Meetings topics center around business intelligence, data storytelling, data literacy, data governance, analytics, and data science. In this conversation with Darren Kaplan, Kim and Darren discuss the importance of improv, empowerment, and mentorship in the world of data science.Kimberly LinkedInhttps://www.linkedin.com/in/kimberlyherrington/The Data Standardhttps://www.linkedin.com/company/the-data-standard/https://datastandard.io/
Blogging and competing on Kaggle are valuable tools to any data scientist. Matt discusses his experience with data science blogging and competing on Kaggle, and how they've helped his career as well as his journey to becoming a better data scientist. Join us in this episode as we explore some of the benefits and pitfalls of data science writing and competing.Matt LinkedIn: https://www.linkedin.com/in/matt-yates-67321678/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Recently, there has been a growing focus on the benefits of mindfulness. Are you curious about how to get started with mindfulness? Ready to dip your toes into this daily practice? Or maybe you need some encouragement, perhaps some fresh inspiration to get back into your daily practice. If so, this podcast is for you.Loryfel LinkedIn: https://www.linkedin.com/in/lorynunez/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data governance is a complex endeavor, but scaling it to meet the needs of a complex or globally distributed organization requires a well-considered and coherent strategy. If you are struggling to scale data quality controls and governance requirements then this interview will provide some useful ideas to incorporate into your roadmap.Deron LinkedIn: https://www.linkedin.com/in/deronhook/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Meet Raghu Dhara, the Head of Data Science at KeepTruckin. He is a Harvard grad who founded a start-up from his dorm room and was also a staff writer on the Harvard Crimson newspaper. In this episode, we discuss Data Science Workflows and how it’s becoming a growing area in data science.Raghu LinkedIn: https://www.linkedin.com/in/rdhara/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
One of the biggest problems facing legacy banking organizations today is leveraging data and advanced analytics to drive digital transformation, creating hyper-personalized experiences, supporting an innovative culture, and solving consumer challenges with appropriate technology.Sandeep LinkedIn: https://www.linkedin.com/in/sandeepkoul1982The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
This week on the Data Standard, we chat with Sudaman about building a good data architecture. When talking about a data warehouse architecture, or even just a data architecture, people often think about building the data warehouse and specifying the server hardware, building the ETL, things like that–they tend to lose sight of the larger picture of data architecture. We are super excited to have Sudaman on the show with us this week.Stephanie LinkedIn: https://www.linkedin.com/in/sudaman/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Barr Moses is the Co-founder & CEO of Monte Carlo, a company on a mission to accelerate the world’s adoption of data by improving data reliability and reducing data downtime. Prior to founding Monte Carlo, Barr built the customer data and analytics team at Gainsight, where she helped grow the company 10x in revenue. From a silent retreat to building a robust community of data leaders, Barr is setting an impressive example for aspiring founders.Barr LinkedIn: https://www.linkedin.com/in/barrmoses/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Anthony offers a valuable perspective on where AI is taking financial services. Episode topics include: AI-driven risk measurement, risk prediction, and risk mitigation.Anthony LinkedIn: https://www.linkedin.com/in/anthonyjerkovic/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Kurt is an experienced Information Technology Manager with a demonstrated history of working in the insurance industry. Skilled in Analytical Skills, Databases, Team Building, Management, and Start-ups. Strong information technology professional with a Bachelor’s degree focused in Management Information Systems and Finance from Ohio University.Kurt LinkedIn: https://www.linkedin.com/in/kurt-tighe-20802371/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data and advanced analytics are the foundation of every organization. Beyond improving efficiency and understanding business success, the power of data and predictive modeling can improve the understanding of consumer needs and personalize experiences. Today, we discuss how data and advanced analytics is a matter of survival for financial institutions, consumers and even in their personal lives.Seyi LinkedIn: https://www.linkedin.com/in/seyiogundeji/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data integration is a critical piece of every data pipeline, yet it is still far from being a solved problem. There are a number of managed platforms available, but the list of options for an open source system that supports a large variety of sources and destinations is still embarrassingly short. If you are struggling to maintain your extract and load pipelines or spending time on integrating with a new system when you would prefer to be working on other projects then this is definitely a conversation worth listening to.Stephanie LinkedIn: https://www.linkedin.com/in/bquach/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In the latest episode of the Data Standard Audio Experience, we sit down with Rich Liebling, Director of Data Engineering at Course Hero, and talk about the inner workings of data engineering, analyst, and scientists teams. Learn more about best practices for high functioning data orgs, pitfalls to avoid, and how these teams are continuing to evolve in the latest episode of Data Standard.Stephanie LinkedIn: https://www.linkedin.com/in/richliebling/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
This is one of the most energizing episodes we’ve had in a while. This is valuable for people at the early stages of their careers. We discuss internships, applications of data science in different industries, how to structure a career journey and choose companies, how you can utilize luck, how to network and be genuine in networking, and a lot more.Lewis LinkedIn: https://www.linkedin.com/in/lewisking/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
The topic of today’s podcast episode is being authentic to yourself. We’re going to answer the question: What does being authentic mean? Alessia shares tips on how to find your authentic self.About our host:Laura Edell Chief Data Scientist, AI Markets & Innovation @ Microsoft https://www.linkedin.com/in/lauraerinedell/About our guest: Alessia Bellhttps://www.linkedin.com/in/alessiabell/The Data Standardhttps://www.linkedin.com/company/the-data-standard/https://datastandard.io/
In this episode of the Data Standard, we talk at length about how someone can break into sports analytics as a career and Ken’s youtube channel.Ken LinkedIn: https://www.linkedin.com/in/kenjee/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Causality and causal modeling is one of the hottest topics in machine learning.Jasper LinkedIn: https://www.linkedin.com/in/jasperseldin/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
A “White Space Analysis” represents custom research that provides an analysis of a given technology, capability, and/or solution set within an ecosystem. It typically includes a value chain assessment and gap analysis in terms of market needs (current and anticipated) vs. existing offerings. It also includes a competitive assessment of “who is doing what” and “how well are they doing it”.The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data quality is important to the business. That you know. But do you understand what it takes to provide data quality. In this podcast, we’ll review how data quality problems can arise. Briefly defined, data quality refers to the ability of a data set to serve whichever need a company hopes to use it for. That need could be sending marketing materials to customers. It could be studying the market to plan a new product feature. It could be maintaining a database of customer data for help with product support services, or any number of other goals.Bipin LinkedIn: https://www.linkedin.com/in/bipinchadha/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, The Data Standard invited Alexis, Head of Data Science at ActZero.ai, to chat about how to better understand how we’re using machine learning models to look at behavioral signals and identify cyberattacks. In their chat, Alexis explains the differences and use cases for techniques such as anomaly detection and supervised learning models.Alexis LinkedIn: https://www.linkedin.com/in/rebecca-burwei/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
“Visualization is a game of decisions.” In this episode, Catherine chats with senior data analyst Sandor Ginsburg.Sandor LinkedIn: https://www.linkedin.com/in/sandor-ginsburg-89952060/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Tong shares about his startup and integrating Actuarial & Data Science to improve health care pricing, forecasting & reserving. TC Tong LinkedIn: https://www.linkedin.com/in/tctong/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Jaekob shares how to lead a product team and how to set a strategy and roadmap towards artificial intelligence.Jaekob LinkedIn: https://www.linkedin.com/in/jaekobchenina/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Catherine interviews Stephanie Sibert, Director of Data at Curology. They talk about Stephanie’s journey into tech. Finally, our hosts wrap the show by discussing some of the struggles that women face in the workplace.Stephanie LinkedIn: https://www.linkedin.com/in/stephaniejsibert/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Sandeep leads a globally distributed team responsible for data science, product engineering, and product support for our AI-based product. Sandeep discusses what machine learning, and more generally artificial intelligence, can be of use for big data application performance management, what are the requirements and challenges of using ML and AI effectively to tackle this problem, and what are the benefits that we can really expect.Sandeep LinkedIn: https://www.linkedin.com/in/sandeepuc/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this interview with Adam Morehouse, Director – Senior Economist, Global Data and Analytics at Dun & Bradstreet, we talk about the increasing importance of data as a vital business asset for the company and explore their journey and top tips to become a more data-driven business.Adam LinkedIn: https://www.linkedin.com/in/adam-morehouse-mba-96719511/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
The longstanding barriers to data sharing between healthcare organizations have been breaking down over the past decade, removing a major obstacle to partnerships between payers and providers. But major challenges remain, as data management only continues to grow in complexity and healthcare organizations try to make sense of a flood of information. Jamie Gardiner joins the podcast to discuss better data management in healthcare.Jamie LinkedIn: https://www.linkedin.com/in/jamie-gardiner-97008a24/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
On this episode, we welcome Kelly Barrett, SVP Data Partnerships at Truthset. Tune into this episode to learn about Kelly’s journey of going from a non-techie to full stack dev.Kelly LinkedIn: https://www.linkedin.com/in/barrettkelly/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
With the proliferation of data sources to give a more comprehensive view of the information critical to your business, it is even more important to have a canonical view of the entities that you care about. Is customer number 342 in your ERP the same as Bob Smith on Twitter? Using master data management to build a data catalog helps you answer these questions reliably and simplify the process of building your business intelligence reports. In this episode Manager of Data Analytics at Dexcom at Tamr, Chuck Miller discusses the challenges of building a master data set, why you should have one, and some of the techniques that modern platforms and systems provide for maintaining it.Chuck LinkedIn: https://www.linkedin.com/in/chuckmillerlinkedin/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Rob speaks about mentoring community teams. Mentoring has evolved to fit the needs of current corporate trends through the years. It goes further now than informal relationships between professions formed through networking. Mentoring is often positioned as a learning and development strategy used to further employee development and increase employee retention. Team mentoring is a flexible derivative of traditional mentoring, with added benefits. It can be defined as multiple mentees and one or more mentors working towards employee development together. These participants are also able to act as the mentee to a mentor, but a mentor to a different mentee simultaneously.Rob LinkedIn: https://www.linkedin.com/in/rob-quish-3433691/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Sasha speaks about his blog and auctioning. Sasha Javid is the Chief Operating Officer at BitPath, the ATSC 3.0 spectrum consortium founded by Sinclair Broadcast Group and Nexstar Media Group. Prior to joining BitPath, Sasha was a communications attorney at Hogan Lovells, and also the Chief Data Officer and Legal Advisor on the FCC’s Incentive Auction Task Force.Sasha LinkedIn: https://www.linkedin.com/in/sasha-javid-8a31803/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
When people think about artificial intelligence, they often think about what intelligence machines can do on their own, without human interaction. However, some of the most powerful and useful AI systems are those that help or augment human capability. The idea of AI systems that augment human ability is known as augmented intelligence. Daniel Byler shared his perspectives on the power of AI as applied to augmented intelligence.Daniel LinkedIn: https://www.linkedin.com/in/danielbyler/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Austin is a data scientist who loves creating machine learning applications in business. He has a history of success in delivering on large initiatives in different areas of IT using modern ML tools and methods (Python, Spark & deep learning architectures). He was the first hire by the CTO at Kaiser Permanente to work on enterprise big data and AI projects as well as in his current role at Stanford Children’s Hospital.Austin LinkedIn: https://www.linkedin.com/in/aus10powell/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In recent years, organizations have opted to collect vast amounts of data assuming that, if they harvest enough of it, it will eventually give rise to relevant business insights. As the landscape evolves, however, it’s becoming evident that more data isn’t necessarily better. After all, the more data an organization has to wade through, the more difficult it is to separate the valuable business information from the irrelevant. A data insights strategy is built on the premise that to realize the true potential of data, you first need to determine why you’re using it and what business value you hope to glean from it. Neeraj joins the podcast to discuss better data strategy & insights.Neeraj LinkedIn: https://www.linkedin.com/in/neerajsane/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Charlie shares some of the work he’s been doing with deep learning and NLP. Linguists have been analyzing language using computer software for the last seventy years, but it’s only recently through AI and deep learning that we’re seeing the true potential of NLP.Charlie LinkedIn: https://www.linkedin.com/in/charles-n-mueller/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
What actually is data science, and what does a data scientist do? What kind of backgrounds do data scientists come from and what skills do you need to be one? In this episode, we start with the basics—declaring once and for all what is data science anyway and exploring how the hype of the field matches reality. We explore the three main areas of data science – analytics, decision science, and machine learning – and help you figure out which is best for YOU.Rebecca LinkedIn: https://www.linkedin.com/in/rebecca-burwei/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode of the Annielytics podcast, host Laura Edell speaks with Vanessa Anderson, Senior Solutions Engineer at CareerBuilder. As globalization advances, it is becoming increasingly important to understand how working cultures differ. Cultural differences have been a major challenge for many workspaces, especially those that are welcoming a variety of different nationalities. About our host:Laura Edell Chief Data Scientist, AI Markets & Innovation @ Microsoft https://www.linkedin.com/in/lauraerinedell/ About our guest: Vanessa Anderson,Senior Solutions Engineer @ CareerBuilderhttps://www.linkedin.com/in/vanderson1/Executive Producer: Darren Kaplan https://www.linkedin.com/in/darrenkaplan500/ The Data Standardhttps://www.linkedin.com/company/the-data-standard/ www.datastandard.io
Host Laura Edell speaks with Alisha Valente, Manager Privacy and Security- TC at Protiviti. Women have played a major role in computing for centuries as well as men. The purpose of this podcast is to gain knowledge on women involved in technology.About our host:Laura Edell Chief Data Scientist, AI Markets & Innovation @ Microsoft https://www.linkedin.com/in/lauraerinedell/About our guest: Vanessa Anderson, Manager Privacy and Security- TC @ Protivitihttps://www.linkedin.com/in/alisha-valente-b4953b18/Executive Producer: Darren Kaplan https://www.linkedin.com/in/darrenkaplan500/The Data Standardhttps://www.linkedin.com/company/the-data-standard/www.datastandard.io
Host Darren Kaplan sits down with Dan McKinley, Senior Director, Data Science & Analytics at Mozilla to talk about working remotely.Dan LinkedIn: https://www.linkedin.com/in/mcfunley/Darren LinkedIn: https://www.linkedin.com/in/darrenkaplan500/
Tatiana Sorokina, Solutions Director, Data Science & Artificial Intelligence at Novartis, joins The Data Standard to talk about being mindful for/to your coworkers.Tatiana LinkedIn: https://www.linkedin.com/in/tsorokinaThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Ioannis Loukakis, Sr. Data Scientist – Digital Growth and Commerce at IBM to discuss finding your passion.Ioannis LinkedIn: https://www.linkedin.com/in/ioannis-loukakis-mba-ms-22ab0737/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Laura Edell speaks with Samira Lowman, VP Organization and Talent Acquisition & Development at GE Digital. In our conversation, we explore the nature of self-compassion, including why it’s such an essential skill for personal growth.About our host:Laura Edell Chief Data Scientist, AI Markets & Innovation @ Microsoft https://www.linkedin.com/in/lauraerinedell/About our guest: Vanessa Anderson, Manager Privacy and Security- TC @ Protivitihttps://www.linkedin.com/in/alisha-valente-b4953b18/Executive Producer: Darren Kaplan https://www.linkedin.com/in/darrenkaplan500/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/www.datastandard.io
In today’s episode of The Data Standard, Darren and Santiago discuss mindfulness to bring out the creativity.Santiago LinkedIn: https://www.linkedin.com/in/santihernandez/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In today’s episode of The Data Standard, Darren and Sam explored how distanced teams can accelerate innovation. Figuring out ways to foster creativity and collaboration in a remote work environment can be challenging. Diving into the world of data science, Sam and Darren discuss the challenges of working from home during the COVID-19 pandemic.Sam LinkedIn: https://www.linkedin.com/in/samuelstrong/Darren LinkedIn: https://www.linkedin.com/in/darrenkaplan500/
On this week’s episode of the The Data Standard Podcast, host Catherine talks with Matt Larriva, Director of Research and Data Analytics at FCP, about best practices for migrating your data. You’ll also learn how to avoid some of the biggest mistakes involved in managing your migration. If you’re considering leaving your legacy system, you won’t want to miss this episode!Larriva LinkedIn: https://www.linkedin.com/in/larriva/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Rasna Goenka, Executive Director at Impact Analytics. Impact Analytics is a fast-growing, enterprise AI software solutions companyRasna LinkedIn: https://www.linkedin.com/in/rasnagoenka/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data can be an intimidating concept, despite the fact that we use it in our everyday decision-making. Calculating a tip based on service and total cost, buying shoes based on how often you’ll wear them, brewing coffee rather than buying Starbucks to save money. When you fully understand what data means, you start making decisions based on data and build it into your processes. Mindfulness, or paying attention to purpose in the present moment, can serve as a tool for qualitative researchers as they navigate the research setting and data collection.Shae LinkedIn: https://www.linkedin.com/in/shaeselix/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Enterprises are increasingly incorporating AI into their project management processes to make projects more strategic and to make better use of the data created by these processes. From AI chatbots to intelligent bots that help automate project management duties such as project documentation and quality check activities, or AI-enhanced data visualization then helps identify bottlenecks and areas where process improvements or other changes can be applied to improve overall performance AI is being used to provide a lot of efficiencies. In this podcast host, Catherine and Alyssa share various ways AI is being used in project management.Alyssa LinkedIn: https://www.linkedin.com/in/alyssa-guo-8991547/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Vinoo Ganesh, Chief Technology Officer at Veraset about large-scale data. Large-scale data analysis is the process of applying data analysis techniques to a large amount of data, typically in big data repositories. It uses specialized algorithms, systems, and processes to review, analyze and present information in a form that is more meaningful for organizations or end-users.Vinoo LinkedIn: https://www.linkedin.com/in/vinoo-ganesh/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In order for analytics and machine learning projects to be useful, they require a high degree of data quality. To ensure that your pipelines are healthy you need a way to make them observable. In this episode, Nivi shares the leading causes of what they refer to as data downtime and how it manifests. Nivi also discusses methods for gaining visibility into the flow of data through your infrastructure, how to diagnose and prevent potential problems.Nivi LinkedIn: https://www.linkedin.com/in/niviarunachalam/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Willem Pienaar, Tech Lead at Tecton about Feature Stores. Feature stores have since emerged as a necessary component of the operational machine learning stack. Feature stores aim to solve the full set of data management problems encountered when building and operating operational ML applications.Willem LinkedIn: https://www.linkedin.com/in/willempienaar/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In today’s episode of The Data Standard, Darren and Raghav covered a lot of ground, from philosophical questions about the definition of fairness to practical challenges that arise when implementing certain ethical AI frameworks.Raghav LinkedIn: https://www.linkedin.com/in/raghavkarnam/Darren LinkedIn: https://www.linkedin.com/in/darrenkaplan500/
Host Catherine Tao speaks with Christopher Iba, Chief Digital Officer at Kleos Live about Chris’s journey and Kleos Live’s new product.Chris LinkedIn: https://www.linkedin.com/in/chris-iba/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Murali Bhogavalli, Product Manager at Tinder. In this episode, Murali speaks about data product management. Every product manager talks about data-driven product management but what is the real explanation of it?To work in this role, you need to understand the complexities of a Data Team, learn how to conduct them, facilitate the ceremonies and manage the development processes in conjunction with specific data science techniques background.Abhishek LinkedIn: https://www.linkedin.com/in/muralidharbhogavalli/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Louis DiModugno, SVP, Chief Data Officer at Hartford Steam Boiler. In this episode, Louis speaks about how schematics allows connection to various data sources.Louis LinkedIn: https://www.linkedin.com/in/louisdimodugno/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Katie Naka, Engineering Project Manager at Wayfair about agile methods for tech teams. Katie brings her experience and ideas on how to improve the role and techniques she use to deliver value within an agile framework.Katie LinkedIn: https://www.linkedin.com/in/katiewins/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Abhishek Kalra, Data Analytics Specialist at Standard Chartered Bank about regulation in the financial crime compliance industry.In this episode, Abhishek speaks about financial compliance trends and regulations. Financial firms can address this problem through tactical responses to regulatory deadlines or think more strategically on how to optimize their compliance data, operations, and technology.Abhishek LinkedIn: https://www.linkedin.com/in/abhishek-kalra-2630115b/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Micah shares his experience about data science interviews. Micah covered topics like what works (and doesn’t) in data science interviews, ways to perform better in these interviews, among other things.Micah LinkedIn: https://www.linkedin.com/in/micahmelling/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Patrick Fernandez, VP/Analytics Manager at Wells Fargo about data in banking and risk management. In this episode, Patrick speaks about using analytics-driven strategies and tools, banks are able to unlock the potential of big data, and to great effect. Implementation of data science in an organization requires a dedicated strategy to avoid sub-par results and information overload. When done correctly, it can offer a competitive advantage, insights, and even new ways to tackle old problems. In a nutshell, risk management through the lens of data science becomes the ability to transform data into action.Patrick LinkedIn: https://www.linkedin.com/in/patrick-fernandez-8737612/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Rachid El Guerrab, Founder and CEO of Stealth Startup and Former Google Director of Engineering. In this episode, Rachid speaks about product management, user experience design, and how we can create the best product experiences for users and our businesses. Also, we discussed how companies in the media and entertainment industry are monitoring social media and integrating social data with other data to form elaborate predictive analytics models.If you’re a manager, designer, engineer, entrepreneur, or marketer who wants to learn the latest best practices this is the podcast you don’t want to miss.Rachid LinkedIn: https://www.linkedin.com/in/rachidelguerrab/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Kathleen Bayles, Director, Business Intelligence & Data Analytics at Happy Money. In this episode, Kathleen speaks about transitioning to cloud-based data storage. As cloud continues to be a high priority of those tasked with delivering technology solutions to their business, it comes with new and complex challenges. Many IT leaders and cloud architects are under immense pressure to get the business to the cloud quickly. We’re sharing some good advice on driving a successful cloud migration from our expert Kathleen.Kathleen LinkedIn: https://www.linkedin.com/in/kathleen-bayles-4a00094/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Justin Gagne, Senior Data Scientist at Very. In this episode, Justin speaks about AI biases and ethics and how AI can help reduce bias, but it can also bake in and scale bias. We’re chatting with Justin Gagne about responsible AI, defining AI ethic terms and collaboration, where does the interest in AI ethics comes from within organisations, how is it ethics for AI is related to good business outcomes, the connection of ethics and risk and much more…Justin LinkedIn: https://www.linkedin.com/in/justin-gagne-a021607b/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Tobias speaks about how the spirit of innovation accelerates hyper-growth for businesses across the globe. Tobias discusses how new approaches to data management are shaping the future of digital transformation.Tobias LinkedIn: https://www.linkedin.com/in/tobias-schuler/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Siddharth Dayama, Senior Manager – Data Analytics at Verizon. In this episode, Siddharth speaks about the value of data from a consumer perspective.Siddharth LinkedIn: https://www.linkedin.com/in/siddharthdayama/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Indrasis Mondal, Senior Director, Data Science, AI, & Product Insights at DocuSign about building AI for a data-driven world. In this episode, Indrasis discusses both tactical and strategical frameworks when it comes to building AI solutions.Indrasis LinkedIn:https://www.linkedin.com/in/indrasisThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Andrew speaks about becoming more empathetic in difficult times. Catherine and Andrew discuss the most effective ways to demonstrate empathy towards others.Andrew LinkedIn: https://www.linkedin.com/in/andrewtener/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Benjamin Young, Data Science & Analytics at AlgoLift. In this episode, Ben speaks about using machine learning/statistical merged approaches and developing robust and accurate algorithms for customer lifetime value (LTV) prediction and for automating user acquisition at scale with the goal of maximizing long-term ROI.Ben LinkedIn: https://www.linkedin.com/in/benjamin-young-53b19aab/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Christina Stathopoulos on empowering women in tech. In this episode, Christina speaks about creating a space that supports women and helps them thrive in the industry.Christina is a regular international speaker supporting data analytics, emerging technologies & women in STEM.Christina LinkedIn: https://es.linkedin.com/in/christinastathopoulosThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Clayton Davis, Head of Data Science at Modzy. In this episode, Clayton speaks about successful data teams and growing talented staff as we innovate the next generation of cutting-edge algorithms and AI tools. Clayton shares the lessons that he has learned while working with dozens of businesses across industries to determine the team structures and communication styles that have generated the best results. If you are struggling to deliver value from big data, or just starting down the path of building the organizational capacity to turn raw information into valuable products then this is a conversation that you don’t want to miss.Clayton LinkedIn: https://www.linkedin.com/in/davisdatascience/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Wes Etheredge - Technical Architect at USAAHost Catherine Tao speaks with Wes Etheredge, a Technical Architect at USAA. In this episode, Wes speaks on the topic of Artificial Intelligence Regulation. He emphasizes the importance of working with data in a highly regulated tech space. Wes LinkedIn: https://www.linkedin.com/in/wesetheredge/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Sudheer Palyam - Senior Director, Data Architecture & Data Life cycle at SalesforceHost Catherine Tao speaks with Sudheer Palyam, the Senior Director, Data Architecture & Data Life cycle at Salesforce. Sudheer speaks about the topic of Data Team Management. Listen to learn more from Sudheer on how his data team has been handling the remote world of COVID-19.Sudheer LinkedIn: https://www.linkedin.com/in/sudheerpalyam/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Jay Egan - Vice President of Data and Business Intelligence at KasasaHost Catherine Tao speaks with Jay Egan, the Vice President of Data and Business Intelligence at Kasasa. Jay speaks about the challenges that come with translating complex data to business value. Jay LinkedIn: https://www.linkedin.com/in/jayegan/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Daniel Scheer - Director of Data Science at StashHost Catherine Tao speaks with Daniel Scheer, the Director of Data Science at Stash. Daniel speaks on the fin-tech industry as well as fraud prevention. Learn more about data infrastructure from the fin-tech industry level.Daniel LinkedIn: https://www.linkedin.com/in/danielcscheer/Catherine LinkedIn: https://www.linkedin.com/in/catherine-taoFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Ylan Kazi - Vice President of Data Science and Machine Learning at UnitedHealth GroupHost Catherine Tao speaks with Ylan Kazi, the Vice President of Data Science and Machine Learning at UnitedHealth Group. On his episode, Ylan speaks about AI Ethics and the importance for companies to emphasize and focus on ethics.Ylan LinkedIn: https://www.linkedin.com/in/ylankazi/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Rizwana Rahman, the Technical Program Manager at Sony Interactive Entertainment. Rizwana speaks about her journey in the tech industry as well as the challenges she has faced to bring herself to a data driven career industry.Rizwana LinkedIn: https://www.linkedin.com/in/rizwana-rahman-517135b/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Shameer Khader - Senior Director of Analytics and Data Science at AstraZenecaHost Catherine Tao speaks with Shameer Khader, the Senior Director of Analytics and Data Science at AstraZeneca. On this episode, Shameer speaks about data within the healthcare industry and the challenges that come with this specific field.Shameer LinkedIn: https://www.linkedin.com/in/khadershameer/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Elliot Stern, the Co-Founder & Chief Data Officer at Marakana. Elliot speaks about his company's product Rival. Learn more about Rival and how the application uses data to innovate the soccer world!Elliot LinkedIn: https://www.linkedin.com/in/elliotastern/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Santiago Hernandez, Head of Data and Reporting at CreditShop, joins The Data Standard to talk to discuss the importance of mindfulness and unifying business and technology teams.Daniel LinkedIn: https://www.linkedin.com/in/danielcscheer/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Keith Belanger - Senior Data Architect at Liberty Mutual InsuranceHost Catherine Tao speaks with Keith Belanger, the Senior Data Architect at Liberty Mutual Insurance. Keith speaks about the importance of the Data Vault methodology. Learn more about how this can improve the tech and business process.Keith LinkedIn: https://www.linkedin.com/in/krbelanger/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Brad Chase, Director of Data Science and Research at RippleCatherine Tao speaks with Brad Chase, the Director of Data Science and Research at Ripple. They speak on the topic of blockchain and the challenges that come with this popular technology.Brad LinkedIn: https://www.linkedin.com/in/bachase/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Nick Ankarstad, Former Director of Strategy, Analytics and Inventory Management at Harris and Harris, Current Director of Analytics at M1 FinanceHost Catherine Tao speaks with Nick Ankarstad, the former Director of Strategy, Analytics and Inventory Management at Harris and Harris. Nick brought great insight on the implications of data within the finance industry. He also speaks on the financial industry as a whole compared to other industries.Nick LinkedIn: https://www.linkedin.com/in/nicklas-ankarstad-cspo-53223332/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with youtuber Scott Peachy to talk about data and how to be empathic to persevere. You can watch ScottyPearchy Youtube "Technically Speaking" every Wednesday @8 pm ET https://youtu.be/dl6OId63eIgYou can connect with Scott Via Linkedin @Scott Peachy Director, Enterprise Data Governance and Quality Assurancehttps://www.linkedin.com/in/scottpeachey/Host Darren Kaplan - https://www.linkedin.com/in/darrenkaplan500/For more information about The Data Standard Visit www.datastandard.io
Dana Cohen, the Director of Data Science at WavemakerCatherine Tao speaks with Dana Cohen, the Director of Data Science at Wavemaker. Dana speaks about the importance of soft skills in the tech industry. Listen to gain insight on soft skills and ways to improve during the Covid-19 Pandemic.Dana LinkedIn: https://www.linkedin.com/in/danaleacohen/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Lisa Palmer, Chief Technical Advisor at SplunkHost Catherine Tao speaks with Lisa Palmer, the Chief Technical Advisor at Splunk. Lisa speaks on how to make optimized decisions with AI. Throughout the podcast, Lisa also touches on how data has been able to help research some environmental challenges.Lisa LinkedIn: https://www.linkedin.com/in/palmerlisac/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Krystal Maughan, current PhD at University of VermontHost Catherine Tao sits down with Krystal Maughan, a current PhD at the University of Vermont. Krystal speaks on the topic of differential privacy and provable fairness. Learn more about her take on privacy and fairness.Krystal LinkedIn: https://www.linkedin.com/in/krystal-maughan-3563a215/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Dave Jaw- The Director of Data Science at TrupanionHost Catherine Tao speaks with Dave Jaw, The Director of Data Science at Trupanion about the significance of data in the medical pet health insurance industry. Dave speaks about some of the successes and challenges he has faced when building up the data science sector at Trupanion. Listen to learn how data is being used for your pets!Dave LinkedIn: https://www.linkedin.com/in/david-jaw-106022116/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Shiva Amiri, Director of Data and Research Infrastructure at 23andMeHost Catherine Tao speaks with Shiva Amiri, Director of Data and Research Infrastructure at 23andMe. Shiva speaks about Digital Biology and how data has been used to help the biotech industry. Listen to learn more about her take on innovative technologies.Shiva LinkedIn: https://www.linkedin.com/in/shivaamiri/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Steve Morin, Head of Mobile Engineering at AsanaHost Catherine Tao speaks with Steve Morin, Head of Mobile Engineering from Asana. Steve speaks about some of the best practices to improve the management of different data teams. Gain insight on how to lead your data team to success!Steve LinkedIn: https://www.linkedin.com/in/stevebmorin/https://productivegrowth.substack.com/ https://twitter.com/stevemorinCatherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Sai Ravuru, Data Science Manager at AllegiantHost Catherine Tao speaks with Sai Ravuru, a Data Science Manager at Allegiant. Sai speaks about how the innovative technologies with data science are used in the aviation industry. Listen to learn more about how his field is changing tech.Sai LinkedIn: https://www.linkedin.com/in/sairavuru/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Edwin Covert, Director of Security Assessments and Infrastructure Engineering and Architecture at WarnerMedia Host Darren Kaplan sits down with Edwin Covert, a cybersecurity professional at WarnerMedia. They cover how to keep up morale in a completely remote team, zoom from a security standpoint, and address the fact our phones are listening to us. Tune in to hear this fun and informational episode. Edwin's Linkedin: linkedin.com/in/ecovertDarren's Linkedin: linkedin.com/in/darrenkaplan500For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Bryan Williams, VP of Data Science at TONIK+Host Darren Kaplan speaks with Bryan Williams, the VP of Data Science at TONIK+ on the Evolution of the Data Space over time. Hear about Bryan's thoughts on how the younger generation is consuming knowledge and how they are learning quicker than ever before.Bryan LinkedIn: https://www.linkedin.com/in/bnwilliams56/Darren LinkedIn: https://www.linkedin.com/in/darrenkaplan500/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Todd Anello, Chief Data Architect at NationwideHost Catherine Tao speaks with Todd Anello, the Chief Data Architect from Nationwide, on the topic of Data Democratization. Todd gives insight with tips and tricks for how companies can achieve success and improvements in their businesses.Todd LinkedIn: https://www.linkedin.com/in/toddanello/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Benjamin Rogojan about exactly what is Consultant Data Engineering and his journey to this career. Rogojan speaks on the holistic approach that Data Engineers must employ at different companies and utilizing the rising popularity of data warehouses. Join us to listen to Benjamin's advice on how to be a successful consultant. Benjamin's LinkedIn: linkedin.com/in/benjaminrogojan Twitter: https://twitter.com/SeattleDataGuyCatherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Show Theme: Non Relational Data and Linkedin Trolls with VP Cloud & Data Engineering Guest: Simon Aloyts Host Catherine Tao speaks with Simon Aloyts, VP of Cloud & Data Engineering at Itransition Group. Aloyts speaks on how data is gaining volume and variety, and how analytics must change to accompany this. Tao and Aloyts address the types of trolls and bots we see on linkedin and their motives. Simon's Linkedin: linkedin.com/in/aloytsCatherine's Linkedin: linkedin.com/in/catherine-taoFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Ryan Deeds, VP of Data at Assurex Global and "Data Practitioner" to discuss the importance of being able to adapt in tech as static knowledge becomes obsolete. Tune in to hear an engaging conversation about the value of being a lifelong learner and what it means to be in kind in a post-covid world. Ryan's Linkedin: linkedin.com/in/ryancdeedsDarren's Linkedin Profile www.linkedin.com/darrenkaplan500For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao speaks with Nuzhi Meyen, CEO of Helios P2P, a peer-to-peer financing platform, about how Data Driven Transformation is necessary for a company to maximize its success. Meyen speaks about the benefits of this transformation, how to begin implementing it within your company, and some of his best practices at Helios P2P. Join us to listen to Meyen's words on getting the most out of a company's data. Nuzhi's Linkedin: linkedin.com/in/nuzhi-meyen-20b077125medium.com/@NMeyenCatherine's LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Catherine Tao sits down with Nick Heudecker, former Research VP at Gartner (current Senior Director of Market Strategy and Competitive Intelligence), to speak about the topic of DataOps. Nick speaks on the importance of DataOps and how companies need to have structure and organization to build successful businesses. Learn about how you can use DataOps to improve your tech team.Nick LinkedIn: https://www.linkedin.com/in/nick-heudecker/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan speaks with Alon Honig, the Vice President of Cloud Data Architect at Sotheby’s, about building high performance data teams and the importance of mindfulness. Alon was also kind enough to share a few of his tips and tricks on how to improve mental health during this time of remote work.You can connect with Alon and Darren via LinkedinAlon’s LinkedIn: https://www.linkedin.com/in/alonhonig/Darren LinkedIn: https://www.linkedin.com/in/darrenkaplan500/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Show Theme: Problems Which Chief Data Officers EncounterGuest: Kevin M Lewis, Director of Data Strategy and Governance at TeradataHost Catherine Tao speaks with Kevin M Lewis, Director of Data Strategy and Governance at Teradata, on the issues which chief data officers come across and how to find solutions to them. Kevin gives insightful, detailed tips and tricks on the ideas of “The Wild Wild West” and “Overcorrection”. Join us to listen about Kevin’s advice on how to be a stronger chief data officer.Kevin LinkedIn: https://www.linkedin.com/in/kevin-m-lewis-88058b19/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Show Theme: Collaboration in the Tech Data SpaceGuest: Andrew Karcher, Senior Principal Data ArchitectHost Catherine Tao speaks with Andrew Karcher, Senior Principal Data Architect at BD, on the topic of Collaboration in the Tech Data Space. In this episode, Andrew speaks about various resources which can help data enthusiasts get a head start on their careers. Listen to learn more about enabling others to work well amongst a team setting.Andrew LinkedIn: https://www.linkedin.com/in/andrewkarcher/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
How AI is Impacting the Climate CrisisNarayanan Subramaniam, Senior Staff Architect + Director of EngineeringHost Catherine Tao speaks with Narayanan Subramaniam, Senior Architect and Director of Engineering at Nutanix, on the topic of AI and the Climate Crisis. AI has made important contributions to our society by thoroughly analyzing our data over the past decades. Learn about how the IEEE Humanitarian Conference informs our world about the major long term impacts of climate change. Narayanan LinkedIn: https://www.linkedin.com/in/cnsubramaniam/Catherine LinkedIn: https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Netflix's Bhargavi Reddy Dokuru, joins The Data Standard to talk about Data Engineering in the Workplace.You can connect with Bhargavi Reddy Dokuru and Catherine Tao via LinkedInBhargavi Reddy Dokuru https://www.linkedin.com/in/bhargavidokuru/Catherine Tao https://www.linkedin.com/in/catherine-tao/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Bk Vasan, From T-Mobile. BK is responsible for transforming the Enterprise data organization to a Cognitive Intelligence organization. You can connect with Bk Vasan and Catherine Tao via Linkedin Bk Vasan https://www.linkedin.com/in/bk-vasan-3126a256/Catherine Tao: https://www.linkedin.com/in/catherine-tao/ For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with IBM's Sumit Gupta, VP of AI Strategy & CTO, Data & AI to talk about Micro Pivoting and AI.Sumit: https://www.linkedin.com/in/sumitg/Darren: https://www.linkedin.com/in/darrenkaplan500/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Bala Natarajan, Director of Big Data Platform Engineering at PayPal, joins The Data Standard on the topic of big data transformation in payment technologies. You can connect with Bala on LinkedIn at https://www.linkedin.com/in/bnataraj/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Laura Edell Chief Data Scientist, sits down with Catherine Devine Microsoft's Worldwide Education Business Strategy Leader to talk about Women in Technology, Libraries and Museums.Follow Laura and Catherine on Linkedin!Laura Edell https://www.linkedin.com/in/lauraerinedell/Catherine Devine https://www.linkedin.com/in/cmdevine/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Laura Edell speaks with Genevieve Graves, PhD and Founder of EyeO about Women In Tech and Curry Combing to get data / insights during a conversation.Connect with Genevieve and Laura on LinkedinLaura Edell - https://www.linkedin.com/in/lauraerinedell/Genevieve Graves, PhD. - https://www.linkedin.com/in/genevievegraves/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Annielytics Host Laura Edell sits down with Nandini Malik, Data Scientist from Aetna to talk about Women in Tech and the Imposter Syndrome. You can connect with Laura and Nandini on LinkedInNandini Malik https://www.linkedin.com/in/nandinimalik/Laura Edell https://www.linkedin.com/in/lauraerinedell/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan talks with Joe Sullivan, Chief Security Officer, Cloudflare about data hacks and Cloudflare.TV. Check out their latest content at www.cloudflare.tvFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Jenny Lin PhD, Senior Data Scientist, Pandora to talk about Data Science for the environment.You can connect with Jenny Lin via Linkedin: https://www.linkedin.com/in/jenny-x-lin/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Patrick Bangert, VP Artificial Intelligence at Samsung to talk about his latest article on The Future Of AI. At Samsung SDSA, Patrick directs the AI Engineering and AI Sciences teams. The AI engineering team develops the Brightics AI Accelerator that provides distributed training and automated machine learning to speed up the creation of an AI model. For more information visit http://www.xcelerator.aiHere is the link to read Patrick's article: https://www.linkedin.com/pulse/status-future-ai-patrick-bangert/Connect with Patrick on Linkedin at https://www.linkedin.com/in/patrick-bangert-452ab013/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with NASA Data Scientist Olga Perera to talk about physics-based transfer learning.You can connect with Olg on linked @ https://www.linkedin.com/in/olga-k-22b7193a/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Angela Shen-Hsieh Director of Innovation at Telefonica to discuss how to innovate using AI and MLYou can get intouch with Angela via linkedin at https://www.linkedin.com/in/angelashenhsieh/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Anup Gosavi, CEO and Co-Founder of Spext.co the leading podcast editing software.For more information about spext visit www.spext.coFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Jared Rosen, Chief Visionary Officer at DreamSculpt Books and Media to talk about storytelling tips. Writing a book can be scary and difficult. Jared shares his best practice advise on how to get started.For more information about Dreamsculpt visit their website https://dreamsculpt.com/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Vin Vashishta to talk about frontier vs laggard companies in the ML Space.You can follow Vin on Twiitter @v_vashishtaFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Laura Edell to discuss AI Sustainability and how to use AI for the betterment of a community and augment it with social outcomes. You can learn more about Laura's work and follow on GitHub https://github.com/annedroidFor more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode Host Darren Kaplan talks with Mathew Joseph about how AI is reinventing banking to become a financial partner to every customer.You can connect with Mathew on LinkedIn @ https://www.linkedin.com/in/mathewjoseph7/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Brian Monteiro PhD, Chief Analytics Officer at Inspired Intellect to talk about building a use case to get your initiative funded. To learn more about Inspired Intellect visit their website: https://inspiredintellect-us.com/For more information about The Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Ron Koller to discuss Digital Change Management and Social Science to get from point A to point B.Connect and follow Ron via LinkedIn to learn more about the work he is doing with IBM https://www.linkedin.com/in/ronkoller/For more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Daren Kaplan sits down with Sanjay to talk about the business impact of setting the technology direction of an organization. This will is one of our favorite discussions because it impacts start ups and enterprise companiesFor more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/Connect with Sanjay Basu on Linkedin https://www.linkedin.com/in/sanjaybasu/
Host Darren Kaplan sits down with Dan Becker CEO and Founder of Decision.ai to talk about pricing models.For more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
For more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan talks with Nandini Malik about Experiment Design. For more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Data Standard Audio Experience Host Darren Kaplan sits down with Tim Eller to talk about his new company dcyd. dcyd is the most intuitive and informative ML model performance monitoring SaaS. Think NewRelic for AI. dcyd watches the watchmen.https://www.dcyd.io/For more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with Takashi Ueki about Work From AnywhereFor more information about The Data Standard please visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode, Darren Kaplan sits down Marc Rind, VP Software Development and Data Analytics at Fiserv to discuss synchronous collaboration tools.For more information about the Data Standard visit our website at www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Alison McCauley best-selling author of Unblocked sits down with The Data Standard to talk about the business and cultural impacts of Blockchain.Host Darren KaplanFor more information about The Data Standard visit www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/For more information Alison McCauley and her best-selling book Unblocked visit: https://www.alisonmccauley.io/
Host Darren Kaplan and Kurt Cagle discuss the new norm of removing Corporate Geofencing as a result of remote work. For more information about the Data Standard visit https://datastandard.io/The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Show Notes:In this episode host, Darren Kaplan talks with Kaggle expert and soon to become Ph.D. Max Halford about how to amplify your data science work and research by sharing it on Medium, Github, and Kaggle competitions. Check out Max's opensource library for online machine learning https://github.com/creme-ml/cremeAnd for more information about The Data Standard visit us at www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this episode host Darren Kaplan sits down with Cyber Security Data Scientist and Author Charles Givre to talk about End-to-End encryption and the new API tool he is building.As many of around the world work from Video collaboration tools like Zoom, Google Hangouts, and Microsoft Teams are the new normal. What is the business impact of end-to-end encryption and why does it matter? Rest APIs are also hot right now. Charles shares a new platform he built for the enterprise. For more information about his tool check out his video. https://www.youtube.com/watch?v=oEOhFWm3D9A&t=739sHost Darren Kaplan https://www.linkedin.com/in/darrenkaplan500/Guest: Charles Givre https://www.linkedin.com/in/cgivre/For more information about The Data Standard visit http://www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Host Darren Kaplan sits down with The Good Factor CEO and SEO Ali Bouhouch to talk about how to get your data science initiative funded. The Good Data Factory is a team of Data and Algorithm professionals bent on changing the way AI, Data Science and Machine Learning are used to transform business and society at large for a better, more sustainable and more human experience. www.thegoodfactory.comFor more information about The Data Standard go to https://www.datastandard.ioThe Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
In this podcast, we cover:- A quick intro to blockchain technology and cryptocurrency- How this relates to virtual worlds and digital economies- Why Ready Player One defined an economy that would need blockchain technology- Trends shaping the world today- Rev (revstarts.com), an online accelerator helping founders tackle meaningful opportunities from day 1.The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
“You can think of Presto almost like a database, but it’s more of an abstraction layer for a large group of databases” – Josh Odmark, CTO & Founder of Pandio.
In this episode of The Data Standard, Darren Kaplan is joined by the CTO & Founder of Pandio, Josh Odmark. Josh is a full-stack engineer expert that worked with PHP, Python, Ruby, JavaScript, and SQL.
As an engineer working in many different technologies, it’s interesting to hear what Josh has to say about Presto and how he uses it for public data around museum information. Josh joins us to talk about how he uses Presto by Facebook and gives us a quick demo of his approach and the benefits that he thinks are most valuable.
Presto is a distributed SQL query engine. It’s an open-source Facebook technology and can be adjusted to anyone’s needs. It gives users a completely different approach to querying data. Traditionally, data is copied or moved into some warehouse, but Presto doesn’t do that; it lets you query data in place.
But Presto requires access to a flat file or database. To show this as an example, Odmark downloaded data from the Museum of Modern Art from their open-access database. There’s no need for any kind of preparation, simply download the file and open it.
Even though this file requires a bit of ETL, it’s not an issue since Presto lets users run SQL against these kinds of data sets and open up many options. The second data set that he used was from The Metropolitan Museum of Art. Both of these files are typical CSVs.
Using the AWS s3 Presto one-click install, you can instantly run Presto within AWS. This allows users to run SQL commands against different datasets that have been added to the AWS. Presto’s simplicity is a thing of beauty because users only have to set up the schema and point it to the desired files.
With the “Show Table” command, the user can easily see all of the datasets added visually displayed as tables. These tables have the traditional data frame, including columns and data types. Josh used Presto to set up the table view of the datasets from these two museums in New York.
Even though both museums have different data structures, the platform takes raw files and puts them up in a similar manner and runs SQL queries against them. Odmark showed this on an example where he ran an SQL query against both of the museum datasets to join the two tables based on artist names.
Even though both museums have a different way of storing and structuring their data, Presto can run the query effectively. Still, certain conditionals need to be added, but this is what Presto is about. It gives full SQL capabilities, making it easy to do some ETL actions that will enable you to do your queries.
Presto takes a couple of seconds to run a query against two datasets around 300MB in size. It goes through all the rows and columns to find all of the artist names and display several types of results:
Which artists are displayed or working in both museums;
Which artwork is from a single artist is in one museum, and which pieces of the same artist are in the other museum;
Presto has a query planner that adjusts the query that has been added. This way, it allows the same query to run effectively against different clusters of data. Despite these complex processes going on in the background, the execution is really fast.
Even though he used two files to simulate databases, Presto lets users add multiple databases and files and works in the same manner. Presto can connect many different types of data but also connect things within it.
It can query data no matter where it is stored, including services like Cassandra or Hive. It works both with proprietary data stores and relational databases. Simply put, it has the unique ability to combine different data from various sources using queries.
This opens up many opportunities for organizations to do essential analytics quickly that can give valuable answers. At the same time, it’s designed for those analysts, developers, or engineers that need quick solutions.
The results are displayed from a couple of seconds to a couple of minutes, depending on how large the datasets are and how many are there. It’s the best of both worlds when it comes to analytics platforms.
Presto is both quick and free. Even though it already offers some significant benefits, we can expect to see even greater things in the future. As more people use this open-source platform, we will likely see new upgrades and changes that perfect its functionalities and expand its potential.
Make sure to check out the full podcast with Josh Odmark and Darren Kaplan at The Data Standard website.
Fernando Schwartz, Head of AI at Citius Tech shares his thoughts on Data Flattening, Data Bias and The Genetic Non-Discrimination Act.The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/
Harry Kraemer shares his leadership principles with the data standard community. Listen in to learn how to "lead up" with self-reflection.The Data Standard LinkedIn: https://www.linkedin.com/company/the-data-standard/