CDO Matters Podcast: Recent Episodes
Profisee
How can today’s Chief Data Officers help their organizations become more data-driven? Join former Gartner analyst Malcolm Hawker as he interviews on thought leaders on data fabrics, blockchain and more — and learns why they matter to today’s CDOs. If you want to dig deep into the CDO Matters that are top-of-mind for today’s Chief Data Officers, this show is for you.
Most organizations are committing serious capital to AI and can't answer a basic question: how much are we actually spending, and on what? That accountability gap is about to close, whether data leaders are ready or not.
📌 In this episode:
Why fewer than 5% of large companies can accurately track AI spend as a distinct category — and what happens when the CFO gets involved
The Vane Loop framework: a quadrant-based approach to scoring data and AI investments on feasibility and impact across 70+ factors
Why AI architecture decisions are now financial variables — and why most product managers aren't equipped to make them
The strategic case for decommissioning: why building a library of reusable skills beats running 200 half-finished use cases
💬 The takeaway: "If you don't manage your costs, your costs will be managed for you." — Malcolm Hawker, Episode 104
About the host + guest: Malcolm Hawker is a former Gartner analyst, Chief Data Officer at Profisee, Editor-in-Chief of CDO Matters on Substack, and host of the CDO Matters Podcast.
Karl Ivo Sokolov is Managing Director at Specific Group Austria and co-author of Finance, Grade Data and AI Products. He sits on the US Institute of Management Accountants board and is the creator of the Vane Loop framework for AI portfolio steering.
Every organization is told they need context for AI to work. Almost none of them know where to start. The answer has been sitting in their metadata all along — but most CDOs haven't connected those dots yet.
📌 In this episode:
Why your data catalog is already a source of context — and how to expose it to agentic workflows today
The semantic layer problem: definitions living in BI tools instead of governed catalogs, and why that creates risk
Why engineers and library scientists think about language completely differently — and why that gap matters for AI
Malcolm's argument that CDOs are in a unique position to make a "land grab" on unstructured data before someone else does
💬 The takeaway: "CDOs are in a unique position to make a land grab: the ontologists, the taxonomists, the library scientists are all over the organization without one single leader. That's your moment." — Malcolm Hawker
About the host + guest: Malcolm Hawker is a former Gartner analyst, Chief Data Officer at Profisee, Editor-in-Chief of CDO Matters, and host of the CDO Matters Podcast. Ole Olesen-Bagneux is Chief Evangelist at Actian and O'Reilly author of Fundamentals of Metadata Management (2025) and The Enterprise Data Catalog (2023) — the practitioner's reference for anyone building or governing a data catalog.
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Guest Ole Olesen-Bagneux → https://www.linkedin.com/in/ole-olesen-bagneux/
Most organizations default to replicating data: copying it from source systems into warehouses and lakes so their tools can reach it. Anu Jain, founder and CEO of Nexus One, thinks that's the wrong answer. Malcolm isn't so sure and that's where it gets interesting.
📌 In this episode:
Why the official count of data sources is always an undercount: shadow data, unstructured data, and legacy systems mean the real number is far higher than anyone reports
The case for virtualization over replication: bring the compute to the data, leave it where it lives, and collapse deployment timelines from months to days
"Information yield" — the metric Walmart once reported publicly and stopped, and why AI is about to force every CDO to bring it back
Why centralize-vs-decentralize is a false choice: the Venn diagram reality of golden records, distributed data, and why you need governance across all of it regardless
💬 The takeaway: "Think of CDOs as refineries. You have all this raw data. The question is: how are you enabling your organization to extract value and can you put a metric to it?" — Anu Jain
About the host + guest: Malcolm Hawker is a former Gartner analyst, Chief Data Officer at Profisee, Editor-in-Chief of CDO Matters, and host of the CDO Matters Podcast. Anu Jain is founder and CEO of Nexus One, former CEO of Think Big Analytics, and a veteran of IBM Watson and Teradata. He publishes in Fortune and is active on LinkedIn.
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The data and AI landscape shifted more in the last six months than in the three years prior and most data teams are still operating off roadmaps that predate it. Malcolm Hawker goes solo to give data leaders an honest read on where things stand and what to prioritize for the rest of the year.
📌 In this episode:
- Why Gartner's keynote message — that it's okay to be a late AI adopter — is advice Malcolm thinks is negligent, and why you don't have three more years
- How agentic AI and tools like Microsoft Foundry and OpenAI Studio are finally connecting the dots between data foundations (MDM, data quality, governance) and real AI business outcomes
- What SAP's acquisition of Reltio means for MDM customers and who should be paying close attention
- Profisee named a leader in the new Gartner Magic Quadrant for MDM: what it means and why it took four years to get here
💬 The takeaway: "If you don't have some idea of how you need to adapt your governance model to support AI, you don't have three years to figure it out because you already had three."
About the host: Malcolm Hawker is a former Gartner analyst, Chief Data Officer at Profisee, Editor-in-Chief of CDO Matters on Substack, and host of the CDO Matters Podcast.
🔗 Watch other episodes + read the transcripts on the CDO Podcast page
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For a hundred episodes, the data world has been told data is the center of the universe. It isn't — and three of the most credible voices in the industry are finally saying so out loud. Malcolm Hawker sits down with Scott Taylor, Juan Sequeda, and Samir Sharma for a milestone roundtable: why AI isn't Hadoop, why CDOs keep failing for the same reasons, and what it's going to take to survive what's coming.
Data science teams are delivering results — so why do so many projects never make it to production? Malcolm Hawker and Kristen Kehrer, founder of Data Moves Me and former data science leader, dig into the organizational failures behind the disconnect: governance that blocks data access, business stakeholders who hand scientists solutions instead of problems, and why product management may be the missing layer in your data org. They also get into what AI actually means for data science careers, whether junior roles have a future, and how staying relevant now means building things — fast.
The market for data leaders is growing - but the CDO role itself may be under pressure.
In this episode, Malcolm Hawker and Kyle Winterbottom explore why organizations are questioning data leadership value, how AI is reshaping career paths, and what separates those who advance from those who stall.
If you’re navigating your next move in data, this is a conversation you can’t afford to ignore.
Episode OverviewIn this episode of CDO Matters, Malcolm Hawker sits down with Yext Chief Data Officer Christian Ward to explore how AI is fundamentally reshaping the relationship between data and modern marketing.
As traditional playbooks built around search, SEO, and paid media begin to fracture, the conversation dives into what this shift means for CMOs—and why CDOs must step into a far more consultative and strategic role in guiding how organizations prepare their data for an AI-mediated customer journey.
The result is a thoughtful discussion on the emerging data realities behind AI-driven discovery, and what data leaders must do today to ensure their marketing partners remain visible, relevant, and competitive in an AI-first world.
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Episode OverviewIn this episode of CDO Matters, host Malcolm Hawker speaks with Samir Sharma about the idea behind the Data Strategy Canvas and how organizations can bring more structure to their data initiatives.
They discuss how frameworks can help leaders connect data strategy to real business priorities and improve alignment across teams. The conversation explores practical ways data leaders can simplify complex strategy discussions and move from vision to execution.
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Episode OverviewIn this episode of the CDO Matters podcast, I sit down with Microsoft’s Karthik Ravindran to unpack what it really means to be “AI-ready” in 2026, and why most organizations are still thinking about data the wrong way.
We explore the collision of product management, governance, and platform strategy, and why AI success will be determined less by models and more by mindset, operating model, and the quality of the data fueling the engine. If you’re a data or analytics leader trying to translate AI hype into measurable business outcomes, this is a conversation you won’t want to miss!
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Episode OverviewIn this episode of CDO Matters, Malcolm Hawker sits down with Sarah Levy, the CEO of Euno, to unpack why traditional data governance is collapsing under the weight of AI.
They explore how context, metadata, and probabilistic thinking are redefining what “AI-ready” really means - and why CDOs who don’t adapt quickly risk becoming irrelevant.
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Episode OverviewIn Episode 93 of the CDO Matters podcast, host Malcolm Hawker sits down with Eric Overby, Faculty Director at Georgia Tech, for a thoughtful conversation on professional development in data.
From building lasting skills to staying relevant as the field evolves, they explore what it takes to grow a meaningful, resilient career in today’s data-driven world.
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Episode Overview In this episode of the CDO Matters Podcast, Malcolm Hawker lays out his most candid and contrarian predictions for where data, analytics, and AI are really headed in 2026—cutting through the hype to focus on what will actually matter for data leaders.
From the evolution (and fragmentation) of the CDO role to hard truths about AI readiness, governance, and operating models, this episode challenges conventional wisdom and calls out uncomfortable realities many organizations are still ignoring. If you’re responsible for turning data into outcomes, and not just headlines, this is a must-listen.
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Episode OverviewThe data world loves trends — but most of them don’t survive contact with reality. In this annual Top Ten Trends episode, Malcolm Hawker reflects on the year that was, exposing where data leaders made real progress and where they kept repeating the same mistakes. Expect honesty, uncomfortable truths, and a few sacred cows put out to pasture.
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Episode OverviewIn this episode, Malcolm sits down with Jeremi Karnell of InvestNet to explore how the company is transforming six trillion dollars of “digital exhaust” into powerful decision-intelligence capabilities for financial advisors.
Jeremi explains how predictive models, knowledge graphs, and generative AI are reshaping advisor workflows, driving measurable revenue lift, and redefining what modern data products look like in financial services. This is a rare look at an AI success story in an industry where most POCs still fail, and a blueprint for any data leader seeking real ROI.
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Episode OverviewIn this episode, Malcolm Hawker sits down with Jonathan Ong, Data Director for Mecklenburg County Public Health, to unpack how a small, resource-constrained team built a thriving data governance program from the ground up.
They explore the practical realities of securing executive buy-in, building data literacy, and shifting governance from a compliance exercise to a catalyst for better decision-making. Whether you lead data in government or the private sector, this conversation offers a playbook for making governance simple, scalable, and impactful.
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Episode OverviewIn Episode 88 of CDO Matters, Malcolm Hawker sits down with Rebecca O’Kill, Chief Data and Analytics Officer at Axis Capital, for a masterclass in pragmatic data leadership. Together they explore how to evolve a data and analytics operating model for a future defined by AI, adaptability, and relentless business alignment.
Rebecca shares how her team turned skeptics into allies by embedding governance into delivery, prioritizing value over frameworks, and embracing a true growth mindset — one built on experimentation, agility, and continuous learning.
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Episode OverviewMalcolm Hawker and DataGalaxy’s Kash Mehdi dive into the evolution of metadata, data products, and AI governance - exploring why traditional data catalogs are no longer enough. They discuss how context, usability, and human insight are reshaping what it means to manage and trust data in an AI-driven world.
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Episode OverviewWhat happens when a seasoned data leader decides to step out of corporate life and build something entirely new? In this episode, I sit down with Dora Boussias—former Stryker executive, dynamic speaker, and now founder of DoraB Global—to talk about her leap into entrepreneurship, the importance of authenticity, personal reinvention, and what it really takes to carve out your own brand in the data space. If you’ve ever wondered what’s possible beyond the traditional career path, this is a conversation you don’t want to miss.
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Episode OverviewEveryone is chasing AI, but few are asking the hard questions about what it really takes to make it work.
In this episode, Malcolm sits down with Ron Green, CTO and co-founder of KungFu.AI, to cut through the hype and talk about what’s actually happening inside companies trying to deploy AI at scale. If you think AI is a plug-and-play silver bullet, this conversation may challenge some of your assumptions.
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Episode Summary Malcolm Hawker and Junaid Farooq unpack one of the toughest challenges in data leadership: moving beyond outdated notions of ownership to embrace accountability and results.
Their conversation sheds light on the mindsets and practices that separate struggling programs from transformative ones.
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Episode OverviewIn this episode of CDO Matters, Malcolm Hawker sits down with Andreas Blumauer to explore how knowledge graphs are transforming enterprise data strategies.
They discuss why semantics and domain models are critical for making data truly AI-ready, and how CDOs can use these tools to bridge the gap between data governance and AI innovation. If you’re leading data initiatives and want to understand the future of knowledge management, this conversation is essential listening.
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Episode OverviewIn this episode of CDO Matters, host Malcolm Hawker sits down with Jonathan Reeve, Chief Product Officer at BetaNXT, to explore the evolving partnership between Chief Product Officers and Chief Data Officers. Their conversation dives into how data can serve as a strategic product, the importance of post-launch customer feedback, and the shift from using AI for individual productivity to driving process efficiency across the business.
They also explore the challenge of scaling products while meeting client demands, and why influence and storytelling are essential skills for product and data leaders. It’s a must-listen for anyone looking to drive innovation through smarter data and AI strategy!
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Episode OverviewIn this episode of CDO Matters, Malcolm Hawker sits down with Raju Mudunuri, Director of Data at Lexmark, to discuss real-world strategies for operationalizing Master Data Management (MDM).
They explore the challenges of stakeholder alignment, platform modernization, and connecting MDM to tangible business outcomes. Whether you're launching your first MDM initiative or scaling one globally, Raju offers grounded insights every data leader can learn from.
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Episode OverviewIn this episode of CDO Matters, host Malcolm Hawker talks with Barr Moses, CEO of Monte Carlo, to break down what data observability really means and why it matters. They explore how leading organizations are using it to catch data issues early, drive trust, and scale reliability— plus where the space is headed next.
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Episode OverviewIn this episode, Malcolm welcomes Mark Stouse back to unpack the Delaware court ruling that's sending shockwaves through boardrooms. They cut through the BS on what fiduciary duty now means for data leaders, why ROI theater won’t cut it anymore, and how CDOs must evolve their approach to value or risk becoming irrelevant.
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Episode OverviewIn this episode of the CDO Matters Podcast, Malcolm Hawker welcomes Jane Urban, the CDAO of Improzo, for a deep dive into the transformative role of data and AI in healthcare.
From predicting patient outcomes to improving care delivery, Jane shares practical insights drawn from her extensive experience. Whether you're in healthcare, pharma, or life sciences, this conversation highlights how data can drive real-world impact.
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Episode OverviewIn this episode CDO Matters, Malcolm Hawker speaks with Gavin Hupp, VP of Technology at United Parks and Resorts, about the balance between long-term planning and short-term adaptability.
Gavin shares how data and AI are used to anticipate guest needs, optimize experiences, and stay resilient amid disruptions like economic shifts and demographic changes.
The conversation also touches on the evolving role of tech leadership, the importance of mentorship, and how data teams can enable agility while staying focused on delivering exceptional customer experiences.
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Episode OverviewIn Episode 76 of CDO Matters, Malcolm Hawker dives into the timely intersection of data and tariffs, exploring how organizations can navigate shifting global trade dynamics with smarter data strategies. With global tensions rising, this conversation is more relevant than ever.
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Episode OverviewEnterprise data isn’t just about governance anymore — it’s about growth, agility, and survival.
Malcolm Hawker and Apurva Wadodkar of Autodesk dive into what it takes to build a data function that keeps pace with change, sharing hard-won lessons and forward-looking strategies along the way.
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Episode OverviewThe expanding data landscape is increasingly complex, making the role of the Data Architect more critical than ever before. On this week’s episode of the CDO Matters Podcast, Pete Cooney, the Lead Enterprise Architect with Jackson, shares his wealth of experience on how CDOs can leverage their data architecture to drive maximum value for their organizations.
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Episode Overview“We are all librarians” is a quote from this week’s guest on the CDO Matters Podcast, Jessica Talisman, the Senior Information Architect at Adobe. In this episode, Malcolm and Jessica go deep on the topic of why Knowledge Management – including many of the concepts practiced for centuries by librarians – is increasingly becoming a ‘must have’ skill in modern data organizations.
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Episode OverviewWhy do companies keep investing in data without seeing results? CDO Matters host Malcolm Hawker and Ken Stott, Enterprise Field CTO at Hasura, explore the Data Doom Loop—a cycle of complexity, tech overload, and stalled progress. Is there a way out? Tune in to find out!
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Episode Overview Have you ever wondered exactly what Data Virtualization is? What about a virtual data warehouse? If you're a CDO eager to learn why Data Virtualization should be a part of a strategy to modernize your data ecosystem, then this episode of CDO Matters with Alberto Pan, the CTO of Denodo, is for you!
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Episode OverviewIn Episode 70 of CDO Matters, Malcolm Hawker explores the future of MDM as AI, cloud migrations, and unstructured data reshape the field. Covering market trends, AI’s role, ROI challenges, and vendor shifts, he shares insights from the latest Magic Quadrant for MDM Solutions to help data leaders refine their 2025 strategy.
Tune in for expert guidance on navigating the evolving MDM landscape.
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Episode OverviewIn this episode of the CDO Matters Podcast, Malcolm and his guest Samir Sharma discuss a wide array of data topics, including the biggest cultural and regulatory differences between Europe and the US and their impact on global data leaders.
While the US appears poised to de-regulate, the influence of growing regulations in Europe, particularly around ESG, are debated in this energetic discussion between two of the data world's most engaging personalities.
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Episode OverviewWhat will 2025 hold for professionals in the world of data and analytics? Join Malcolm Hawker as he shares his top predictions for the year ahead.
From data governance to AI and everything in between, Malcolm unpacks all of the most hype-worthy trends in the data world, cutting through the buzzwords and sharing insights on the topics that will likely be front-of-mind for data professionals over the coming year.
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Episode OverviewData leaders have a massive opportunity to drive transformational value with AI, but many are running on outdated operating models. On this episode of the CDO Matters Podcast, Katharine Shaw Paffett, the Cross Solution AI lead for UK and Ireland at Avanade, shares insights on how CDOs can re-envision their organizations to be more AI-ready. Katharine is at the forefront of the early adoption of GenAI for many large organizations, and her guidance for any company seeking to implement AI is not to be missed.
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Episode OverviewLooking back on 2024, what were some of the biggest, most notable events in the world of data and analytics? Join the host of the CDO Matters Podcast, Malcolm Hawker, and he discussed the death of the data mesh, the growth of the fabric and AI, data products, and many other key data trends that were top of mind for many CDO's over the past year.
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Episode OverviewAre you looking to learn more about Knowledge Graphs, and the role they will increasingly play in a modern data ecosystem? If yes, then you need to check out the latest episode of the CDO Matters Podcast. Sumit Pal, ex Gartner analyst and Strategic Technology Director at Ontotext, shines a light on the world of knowledge graphs, and the important ways they differ from, and complement, more traditional data analysis and persistence methods. If you're a data leader and you're not yet embracing knowledge graphs, then this episode is for you!
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Episode OverviewYour familiar with all the processes your marketing organization is utilizing for managing its data? Are you familiar with the marketing data lexicon, and can you define key terms like onboarding, activating, or harmonizing? Are you working closely with data scientists in your marketing organization?
If you answered no to any of these questions, then you should definitely check out the latest episode of the CDO Matters Podcast. In this episode Malcolm and his guest, Shubh Sinha, the CEO of Integral, go deep into the world of marketing data, and what data leaders should know about this rapidly evolving space.
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Episode OverviewAre you working to become a better leader? Are you seeking insights on the traits and behaviors that you need to develop to become a more authentic, change-oriented leader in your company? If yes, then you need to check out the latest episode of the CDO Matters Podcast, where our guest, Meagan Boson, shares her insights on what it means to be a more authentic leader, and all the ways you and your company will benefit from it.
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Episode OverviewAre you confused about all of the hype around data products? Are you interested in understanding what the benefits of data products are and how you would implement them?
If yes, you need to check out the latest episode of the CDO Matters Podcast as Malcolm cuts through all of the hype around data products to provide clarity on what all data leaders should be conserving around data products, and why.
Listen as Malcolm demystifies the swirls surrounding data products, providing actionable and understandable insights on this popular trend in data.
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Episode OverviewThere are many companies just now evaluating moving all or a portion of their mission-critical data or infrastructures to the cloud. In this episode of the CDO Matters Podcast, cloud computing expert Ayman Husain shares his insights on the key considerations all CDOs must make when considering the role that cloud-based platforms will in their data architectures.
From cost drivers to cloud migration plans and everything in-between, Ayman shares a wealth of insights from years of experience in helping companies move their data to the cloud.
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Episode OverviewNew technologies never exist in a vacuum, and getting value from any new innovation requires the right combination of multiple enabling competencies, including people and processes.
In this episode of the CDO Matters Podcast, Dr. Michael Proksch, author of the Wiley book 'AI Value Creation', shares insights on how some of the biggest global brands are generating value from AI-based solutions.
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Episode OverviewIn this insightful episode of Data Hurdles, hosts Chris Detzel and Michael Burke welcome Malcolm Hawker, Chief Data Officer at Profisee, for an in-depth discussion on the evolving landscape of data management and the role of Chief Data Officers (CDOs) in today's organizations.
The conversation kicks off with Malcolm sharing his journey from product management to becoming a prominent figure in the data management space. He provides valuable insights into his experiences at Dun & Bradstreet and as a Gartner analyst, which have shaped his perspectives on data governance and strategy.
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Episode OverviewAre you struggling to better understand what it means to implement a modern data platform, and why doing so is relevant to your business?
If yes, check out this week’s episode of the CDO Matters Podcast, where Emerson Gatchalian, the CDAO of the Blackbelt Team within Microsoft, shares his insights on how his largest clients and Microsoft are implementing more adaptable, scalable, and AI-ready data infrastructures.
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Episode OverviewJoin the CDO of Profisee, Malcolm Hawker, as he explores the problem of how the increasing prevalence of dark data is playing a role in helping to create a growing sustainability challenge in the world of data and analytics.
Malcolm explores the root of the problem, the impacts its having on the environment, and the practical steps that data leaders can take today to make their data management practices more sustainable.
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Episode OverviewUnlock the secrets to becoming a powerful public speaker and learn how to craft presentations that secure C-level funding for your data projects! Tune in to the latest episode of the CDO Matters Podcast, where Dr. Joe Perez shares invaluable tips and strategies for data leaders and practitioners.
Discover how to captivate your audience, tell compelling stories, and present your ideas with confidence and clarity. Whether you're a seasoned CDO or an aspiring data leader, mastering these skills is essential for your success. Don’t miss out on this opportunity to elevate your public speaking game!
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Episode OverviewIn this episode of CDO Matters, please join Anjali Bansal and Malcolm Hawker as they unpack the intricacies surrounding the journey to becoming a data-driven organization, emphasizing the critical role of data leadership on data culture.
From the nuanced insights gained through real-world experiences to expert perspectives on overcoming cultural barriers, Anjali and Malcolm with explore strategies for cultivating a culture where data takes center stage.
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Episode OverviewSanjeev Mohan is an experienced and knowledgeable expert in the world of data and analytics, and on this episode of the CDO Matters Podcast, he shares his insights on the rapidly evolving world of semantic layers.
Join Malcolm and Sanjeev, both ex-Gartner analysts, as they break down the complexities of these new technologies into simple and approachable concepts, and the important role they will play in the future of the data function.
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Episode OverviewEddie Short is an outspoken and experienced CDO who has managed the data and analytics function for some of the biggest companies on the planet – and he’s recently returned to graduate school with the goal of quantifying the value of Chief Data Officers.
In this engaging conversation, Eddie shares valuable insights from his decades of experience – focusing on a core message that CDOs must develop the leadership skills needed to challenge the status quo and quantify the value of the solutions they provide.
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Episode OverviewWhile many CDO’s inherit large teams, it’s also common for CDO’s to be hired into a role with the expectation they will build a data and analytics function slowly over time.
In this episode of the CDO Matters podcast, Joyce Myers, the CDO of Modern Technology Solutions Inc (MTSI), shares her insights on how she’s overcoming the many challenges that accompany CDOs who are starting small, and are highly reliant on the engagement of other teams for their individual success.
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Episode OverviewJordan Morrow is a visionary thought leader and prolific author in the world of data and analytics, and on Episode #51 of the CDO Matters Podcast, he joins Malcolm to discuss data leadership and building a ‘next gen’ data team.
In this engaging and provocative discussion, Jordan and Malcolm discuss the most important roles and responsibilities that are today missing on most data teams but are increasingly critical to succeed in an AI-driven world of constant change and disruption.
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Episode OverviewIn the 50th episode of the CDO Matters podcast, host Malcolm Hawker delves into a data-driven examination of the podcast's journey. Conducting a thorough review of the past fifty episodes, he identifies notable patterns and insights.
He carefully assesses achievements and identifies areas for improvement, covering a range of aspects, from refining technical elements to strengthening community connections.
Join him as he applies analytical rigor to evaluate past performance and chart a course for future improvement in this landmark episode!
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Episode OverviewThe explosion of LLMs and AI is causing a tectonic shift in the world of data and analytics, and on this episode of CDO Matters, Malcolm and Jon Cooke discuss how CDOs can leverage the discipline of product management to best capitalize on these massive changes.
From data products, to the data mesh, and beyond – Malcolm and Jon enjoy a lively discussion on the many evolving attributes that will increasingly define a world focused less on data (and datasets), and more on knowledge and business insights.
If you’re a CDO and you’re interested in learning more about how your operating model will necessarily need to shift over the coming years to adapt to a new AI-driven world of insights, then this episode is a must-listen.
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Episode SummaryIn an age of constant disruption and AI-enabled business transformation, Master Data Management (MDM) is a must-have capability that all businesses must embrace. In this episode of the CDO Matters podcast, the leading global authority on MDM, Malcolm Hawker, shares his insights on the four keys to successfully and quickly implementing MDM at your organization.
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Episode OverviewIn this episode of the CDO Matters Podcast, Robert Hawker (no relation – at least none that we’re aware of!) joins for a discussion on Practical Data Quality – which is all a programmatic approach to data quality that focuses on business benefits, quick wins, and the highest priority challenges.
Data quality issues are a major hindrance to the AI and digital transformation aspirations of most companies, so having a roadmap to resolve those issues is a strategic imperative for all data leaders. Please join Malcolm and Robert as they discuss a practical, value-driven approach to overcoming the perils of low-quality data.
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Episode OverviewIn a world of exploding volumes of data, the ability to add the context needed to show the complex relationships that exist within and across datasets is of critical importance. Making the jump from data management to knowledge management is a key enabler of a next generation semantic layer, as described by Lulit Tesfaye, a Partner and Vice President with Enterprise Knowledge.
In this 46th episode of the CDO Matters Podcast, Malcolm and Lulit go deep on next gen semantic layers, and how the output of these systems is driving value through improved search, analytics, and generative AI.
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Episode OverviewThe ability of an organization to be more resilient to change, to be more flexible and adaptable, and to use data for decision making – are key traits of high-functioning companies. In this episode of the CDO Matters Podcast, Malcolm talks with Jason Foster, the CEO of Cynosure, about how CDO’s can become more ready for AI, or any other major disruption to their business.
While becoming ‘AI ready’ is extremely important, Jason makes a compelling case that data leaders need to take a more holistic approach to becoming more change resilient – which would also include a focus on value, design thinking, and being more commercially focused – among many other important traits to CDO success outlined in this broad-reaching discussion.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Follow Jason Foster on LinkedIn
Episode OverviewOn this episode of the CDO Matters Podcast, Piethein Strengholt, author of the O’Reilly book ‘Data Management At Scale’, and current CDO of Microsoft Netherlands, shares his perspectives on a variety of emerging technology trends in the world of data, including the data fabric, data products, MDM, AI – and many others – even blockchain for data management.
Malcolm moderates a lively discussion on these trends, with a focus on how data leaders can better understand these concepts, and their value and purpose in a modern enterprise data architecture.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Follow Piethein Strengholt on LinkedIn
Episode OverviewIn this 43rd episode of the CDO Matters Podcast, Malcolm interviews Santona Tuli, a former Nuclear Physicist turned data scientist. Santona shares some provocative and actionable insights to data leaders looking to take a more practical approach to implementing AI and data science into their organizations.
If you’re looking to show value from AI, quickly, Santona shares her recommendations for everything that data leaders should be considering in their search for the optimal way to embrace these transformative new technologies.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Follow Santona Tuli on LinkedIn
Episode OverviewAre you a data professional interested in better understanding what the top trends that could affect your work will be in 2024? What is the future of data products? How will AI influence data governance and data management?
Malcolm covers these topics and many, many more as he shares his perspectives on the direction of the industry of data and analytics in the coming year.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Episode OverviewIn this live episode of the CDO Matters Podcast, Malcolm welcomes Erik Zwiefel, the CDAO of Microsoft Americas. Malcolm and Erik go deep on many of the biggest topics front-of-mind for many CDOs today, including Artificial Intelligence – especially how CDOs can best position themselves and their organizations to be more AI ready, and some practical tips on how to operationalize LLMs within their organizations - today.
Other timely topics for CDOs include the Microsoft Fabric and the concept of ‘One Lake’, a single environment for enterprise data management, persistence, and compute.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Follow Erik Zwiefel on LinkedIn
Episode OverviewIt’s the end of yet another incredibly busy and exciting year in the world of data and analytics, and CDOs looking for an energetic and entertaining perspective on the top trends of the year should put this episode at the top of their podcast playlist.
From the growth of AI to the demise of the data mesh, Malcolm provides his perspectives on the last year in data in a way that only he can – with a witty combination of passion and provocation that will surely leave you wanting more.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Episode OverviewMany CDOs believe that transitioning their companies to a data-driven culture is the #1 roadblock to fulfilling their data strategies. In this episode of CDO Matters, Malcolm provides his insights on what behaviors and mindsets are needed from CDOs to model the culture they wish others outside the data and analytics function to embrace.
Malcolm posits that meaningful culture change must necessarily start within data teams and that until CDOs themselves embrace being more data-driven, they can’t realistically ask others to do the same.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Episode OverviewIn this 38th episode of the CDO Matters Podcast, Malcolm interviews Mark Stouse, the Founder and CEO of Proof Analytics. An accomplished business leader with decades of experience in leading data science initiatives, Mark shares his perspectives on the growing frustration that many organizations are experiencing because of an inability to realize significant benefits from investments in data management and data science.
The risks of CDOs saying they aren’t ‘ready’ to provide business value from AI and data science are real and increasingly unwelcome from companies looking for more immediate returns from their data teams. This is producing an immediate need for CDOs to be unabashedly lean, with an unrelenting focus on a very limited number of specific business needs and outcomes.
Episode Links and ResourcesFollow Malcolm Hawker on LinkedIn
Follow Mark Stouse on LinkedIn
Episode Overview:Many CDOs are hired with the expectation they’ll become the ‘Chief Change Agent’ for their companies – helping to transform old and outdated approaches to data and business management to more digital, efficient, and scalable ones. On this mission many CDOs will most certainly encounter resistance at every level, requiring a deeper understanding of what makes change so difficult.
In this 37th episode of the CDO Matters podcast, join Dan Everett as he helps to explain why people are uncomfortable with change, and how modern data leaders can better lead their organizations through it.
Episode Links and Resources:Follow Malcolm Hawker on LinkedIn
Follow Dan Everett on LinkedIn
Episode Overview:In the 36th episode of the CDO Matters Podcast, Malcolm speaks with Wendy Turner Williams, the ex-CDO of Tableau and VP of Data Strategy for Salesforce. A proven leader in the world of data and analytics, Wendy shares exciting details into her most recent venture, The Association: a community of data and AI practitioners dedicated to helping each other overcome their biggest challenges.
Wendy shares her vision for how this new community will help data leaders finally achieve more influence, more value, and more trust at a time when these things are needed more than ever before.
Episode Links and Resources: Follow Malcolm Hawker on LinkedIn
Follow Wendy Turner-Williams on LinkedIn
Episode Overview: In the 35th episode of the CDO Matters Podcast, Malcolm speaks to Veronika Durgin, the VP of Data with Saks. As a data leader with more of a technical background, Veronika shares her insights on how she's applied the '30% rule' to learn the foreign language of business - a critical key to her success in data leadership.
Throughout the conversation, Veronika shares other practical lessons she's learned that make her such a learned and inspiring member of the data leadership community. Her story shows that with plenty of hard work, a dedication to learning, and plenty of self-awareness, a successful career in data is possible regardless of your background.
Episode Links and Resources: Follow Malcolm Hawker on LinkedIn
Follow Veronika Durgin on LinkedIn
Episode Overview: We live in a world of constant change and massive technical and social disruption, yet the way we manage data has largely remained the same. A continued focus on the same old and tired approaches to data management are no longer serving the needs of data leaders and they must be revisited. In this episode of the CDO Matters podcast, Malcolm explores what it takes to break free of old mindsets that limit the growth and tenure of data leaders, and to embrace more modern forms of data leadership.
Episode Links and Resources: Follow Malcolm Hawker on LinkedIn
Episode OverviewData Engineers play a critical role in enabling the success of any data and analytics function. In this episode of the CDO Matters Podcast, Malcolm interviews Joe Reis, the co-author of the bestselling O’Reilly book, “Fundamentals of Data Engineering”. In the discussion, Joe gives a sneak peek into the minds of data engineers and what makes them tick. Data leaders, particularly those with less technical backgrounds, should find this discussion a helpful tool to improve their relationships with the people critical to the success of their data and analytics operation.
Episode Links and Resources:Follow Malcolm Hawker on LinkedIn
Follow Joe Reis on LinkedIn
Episode Summary:Data leaders have long been challenged by the need to make a tangible connection between investments in data and quantifiable business outcomes. Value Engineering is an evolving competency that CDO’s can integrate into their organizations to solve for this mission-critical need. In this episode, Laurence Young shares his insights as a practiced Value Engineer, sharing his recommendations on the steps CDOs need to take within their organizations to start measuring their business effectiveness.
Episode Links and Resources: * Follow Malcolm Hawker on LinkedIn * Follow Laurence Young on LinkedIn
Episode Overview:While the CDO role gains prominence and importance across most organizations, many CDOs are set up to fail from poorly defined roles, a lack of trust, and an insufficient focus on business outcomes. In this 31st episode of the CDO Matters Podcast, Malcolm interviews Allison Sagraves, the founding CDO of M&T Bank, to ask why so many CDOs face these challenges, and what they must do to overcome them.
In reference to an insightful HBR article Allison recently published on CDO success, she provides her insights on how CDO’s can manage a critical balance between patience and urgency, and the importance of taking the time to recognize where positive strides are being made to deliver on a data strategy. Malcolm reminds CDO’s how important it is to ‘pound the drum’, a metaphor for the importance of marketing – and celebrating – all the strides companies are making towards becoming more data-enabled.
From data literacy, to data quality, to the next generation of data leaders, Malcolm and Allison have a wide-ranging conversation on some of the biggest issues facing data leaders today.
Episode Links and Resources: • Follow Malcolm Hawker on LinkedIn
• Follow Allison Sagraves on LinkedIn
• Read Allison’s article on Harvard Business Review, “Why Chief Data and AI Officers Are Set Up to Fail”
Episode OverviewIn this 30th episode of the CDO Matter Podcast, Malcolm has an inspired exchange with the ‘Dean of Big Data,’ Bill Schmarzo. Bill is an accomplished author, teacher, and C-level executive with a depth of knowledge in building and running large-scale data operations in service of some of the biggest companies in the world.
In the discussion of his most recent book, “AI & Data Literacy,” Bill shares his insights into the six key responsibilities that all consumers of AI must fulfill to optimize their relationship with this transformative technology. In becoming more AI literate, we increase the likelihood that the utility of AI will be maximized for the good of society and not just the corporate bottom line. A critical component of this includes quantifying the concept of ‘ethics,’ which Bill strongly advocates is not only possible, but is absolutely necessary.
Beyond the topic of AI, Bill and Malcolm touch on some of the bigger challenges CDOs face daily, including the importance of connecting data investments to business outcomes and how to potentially solve the ‘value’ equation inherent to every data estate. For CDOs seeking inspiration about the future of data management in an AI-enabled future, look no further than this episode of CDO Matters.
Episode Links & Resources:• Follow Malcolm Hawker on LinkedIn
• Follow Bill Schmarzo on LinkedIn
• Read Bill Schmarzo's new book, 'AI & Data Literacy: Empowering Citizens of Data Science'
Episode OverviewIn this 29th episode of the CDO Matter podcast, Malcolm has an engaging conversation with a long-established thought leader and noted author in the data and analytics space, Tom Redman.
Malcolm and Tom discuss Tom’s recently published book, ‘People and Data,’ where Tom shares his thoughts on the necessity of engaging data consumers to address some of the bigger data-related challenges all organizations face, particularly data quality. Tom shares his recipe for engaging as many stakeholders “without data in their titles” as possible, and the need for CDOs to assert their leadership through an acknowledgment many legacy approaches to data management simply aren’t working, including data governance.
Rather than seeing people as the core problem data leaders need to overcome, Tom makes a strong case that people are, in fact, the solution – especially those outside traditional data roles.
Episode Links & Resources:Follow Malcolm Hawker on LinkedIn
Follow Tom Redman on LinkedIn
Read Tom Redman's latest book, 'People and Data'
Episode OverviewWouldn’t it be great to have a playbook for how to be an effective data leader?
In this episode of CDO Matters, Malcolm has an in-depth conversation with an extremely successful IT and data leader, Renée B. Lahti. With CIO experience spanning multiple industries for some of the best-known brands on the planet — including SC Johnson and Symantec — Renée’s depth of experience shines in this conversation about the current state of the role of CDO, including Renée’s insights on the key factors of CDO success.
Failing fast, redefining value, hiring for diversity and being more agile: These are just some of the many fascinating topics discussed in this episode, which could be considered a playbook for any data leader looking to emulate the success of an accomplished data leader.
Episode Links & Resources:• Follow Renée B. Lahti on LinkedIn
• Learn about the DataEthics4All advisory council
Episode OverviewToday, enterprise data is not only exponentially growing in volume, but in sheer complexity. And how can today’s data leaders extract value if they are unsure where to even start?
In the latest episode of the CDO Matters Podcast, host Malcolm Hawker sits down with Ontotext Chief Marketing Officer Doug Kimball to discuss the wide-ranging applications of next-generation graph database technology.
Listen to Malcolm’s discussion with Doug to learn more about:
• The advantages of graph database technology in particular use cases
• How graph databases can reveal previously unknown relationships
• The speed advantage of graph technology when querying data
• How AI and ML will continue to augment graph technology and reduce human intervention
About the GuestDoug Kimball is the Chief Marketing Officer of Ontotext, a developer of knowledge graph software helping global enterprises gain knowledge and insights from their diverse data. Doug is an accomplished marketing and communications executive and team leader focused on leading strategic growth within global and domestic organizations.
Episode Links & Resources:• Follow Doug Kimball on LinkedIn
• Learn more about Ontotext on their website
As companies grow, they often hire dedicated product managers to oversee all the planning, development and launching a product. Business leaders recognize that this is a critical need and expect products to be managed holistically from ideation to development — so why don’t more companies take that same approach when solving enterprise-wide problems with data and analytics?
On this episode of the CDO Matters Podcast, Malcolm Hawker sits down with Bethany Lyons to discuss her role as KAWA Analytics’ Chief Product Officer (CPO) before diving into a range of timely data topics including:
•“Self-service’ data governance
•Product management approaches
•Centralized security vs. decentralized data modeling
•Enforcing data governance/security policies
•The definition and uses of data build tools (DBT)
•The longevity of CDO tenures
•Key attributes of a good product manager
…and so much more!
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Bethany Lyons on LinkedIn
Visit KAWA Analytics’ website
As we get carried away with modern data trends and new technical developments, it's easy to forget the rich history behind computable data and analytics dating as far back as World War II in the 1940s. Luckily, we have a data historian to remind us!
Host Malcolm Hawker sits down with NY Times Chief Data Scientist (CDS) Chris Wiggins to chat about his new book and dive into what led us to this moment in the data space.
The two discuss:
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The ethics behind using data for social concepts
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Quantifying social data
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Early stages of AI and the creation of data computation
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The history of machine learning
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The internet boom of the 90s
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AI vs. copyright laws
...and so much more!
Episode Links & Resources:Follow Malcolm Hawker on LinkedIn
Follow Chris Wiggins on LinkedIn
Check out Chris Wiggins' new book
Who better to discuss an annual Gartner data summit than a former Gartner analyst himself?
Host and former Garter analyst, Malcolm Hawker, sits down with Profisee's Director of Digital Marketing, Ben Bourgeois, to talk about his experiences and key takeaways after attending this year's Gartner Data & Analytics Summit.
Other topics of discussion include:
- Demystifying the data fabric
- Malcolm's journey in releasing 20+ episodes of the CDO Matters podcast
- Defining data by its business value
...and more!
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Ben Bourgeois on LinkedIn
Register for an upcoming episode of CDO Matters LIVE
ChatGPT. Composable data and analytics. Connected governance. The data fabric.
These are all hot trends and much-hyped tools and frameworks in 2023. But one of the challenges with “bleeding-edge” technologies is a lack of a clear definition — much less a clear guide on how to take advantage of these nascent tools.
Good thing we have a former Gartner analyst with thousands of hours of client inquiries under his belt to help finally demystify one of the most-hyped trends in data management today: the data fabric.
In this 22nd episode of CDO Matters, Malcolm focuses exclusively on providing an extremely “deep dive” into the data management architecture known as the data fabric. The data fabric has gone from relative obscurity to nearly the top of Gartner’s hype cycle in just a few short years. For this reason, forward-leaning CDOs should understand exactly what the data fabric is and how it can benefit their organization.
Starting with a basic definition of a data fabric, Malcolm proceeds to break this rather complex phenomenon down into its component parts — using language that is precise but highly digestible for any non-technical CDO or data leader. Translating the complexity of a fabric into understandable critical capabilities, he shows how a data fabric can eventually be leveraged as a transformational tool for any organization.
For those wondering exactly what capabilities are needed to enable a data fabric, Malcolm reviews the top three capabilities that he believes must be present for any solution to be considered a data fabric. Armed with this information, it becomes clear that the data fabric remains — at least in the short term — an aspiration for most companies given the sophistication and governance maturity needed to enable them.
Malcolm reviews a conceptual architecture of the data fabric and discusses how fabric capabilities will be deeply integrated into — and across — several legacy data management systems, including master data management (MDM), data quality, data governance and data integration platforms. He challenges the notion that any one solution will be used to enable data fabrics — and instead outlines how several software and analytical solutions will need to be deeply integrated to enable fabric capabilities.
Finally, Malcolm ends his demystification of data fabrics by sharing a few key considerations to help CDOs cut through all of the hype related to data fabrics. This includes practical actions data leaders can take now to better position themselves for leveraging data fabrics soon.
Update from Malcolm: This episode was recorded before the production launch of ChatGPT. In the span of just a few weeks, I believe the data fabric has gone from a conceptual framework to something that could easily be envisioned within a modern data estate.
Put another way — if the entire internet before 2012 could be used to train an AI-enabled language model, all your enterprise data could most certainly be used to train AI models that are optimized to support data management use cases. I now believe the data fabric is how AI will be operationalized, at scale, to optimize — and eventually automate — the creation, consumption and management of data within your organization.
I’ve struggled for the last two years to visualize exactly how data fabrics could be implemented at scale, but thanks to ChatGPT, I no longer have this struggle. Hopefully after watching — or listening — to this episode, you come to a similar conclusion.
Key Moments * [7:51] The Hype Behind the Data Fabric * [10:46] Diving Deep into the Fabric * [13:01] Data Fabrics Defined * [21:31] Key Fabric Capabilities * [22:15] Active Metadata * [27:01] Incorporating AI Technologies * [29:56] Synthesizing Metadata with an Intelligence Layer * [35:31] The Data Fabric Architecture * [40:06] Key Fabric Considerations * [52:31] Closing Thoughts
Key Takeaways The Future of the Data Fabric and AI Dependency (12:38)
“We are making a pivot away from people defining the [data governance] rules, the integration patterns, the data quality standards. We are moving away from people deciding that to robots deciding that. That’s a spectrum. We’re largely people-driven today…we’re early in the days of the spectrum from entirely people-driven to entirely robot-driven. We’re early in those days, but where the data fabric goes and the ultimate path here is towards a world highly dependent on the [machines].” — Malcolm Hawker
What Can Metadata Do for You? (17:40)
“What active metadata really means is that, if you had a lot of metadata, and you has some pretty sophisticated analytical tools, and you had some pretty sophisticated new technologies, you could make that data tell you a lot of things about the state of your data enterprise. For example, in theory, you could know when data was accurate or inaccurate.” — Malcolm Hawker
The Current State of Data Fabrics (46:12)
“Data fabrics don’t exist yet. You can’t go buy one. There is a ton of promise here. But between where we are, and where we need to go and between concept and theory, there are some really major roadblock issues we need to overcome. And frankly, there’s a lot of technology that doesn’t even exist yet.” — Malcolm Hawker
EPISODE LINKS & RESOURCES: Follow Malcolm Hawker on LinkedIn
Acquiring expertise in any field is a tool that is sharpened over time, not overnight. This is especially true for the complex world of data and analytics. It takes drive, passion and experience to become a credible data leader.
For this episode, Malcolm joins datazuum CEO and Founder, Samir Sharma, on the Data Strategy Show podcast to answer personal and professional questions that provide insight into who Malcolm is as a data thought leader both in and out of the office.
Throughout their discussion, Samir asks a series of rapid-fire questions covering several topics including:
- Personal interests
- Memorable life experiences
- Professional insights
- Outlooks on the data space
- Sources of inspiration
- Leadership qualities
- Current trends and happenings in the world of data and analytics
And so much more!
Key Moments[1:30] Rapid-Fire Questions with Malcolm
[8:30] Three Things Malcolm Can’t Live Without
[17:50] Current Inspirations in the Data Space
[24:45] Malcolm’s Professional Epiphany
[45:14] Advice for Data Leaders
[53:20] The Problems with Data Literacy
[57:55] Malcolm’s Highlight of the Year
[1:01:25] Malcolm’s Personal Leading Style
[1:03:05] Common Data Challenges
Key Takeaways Current Data Inspiration with Blockchain (17:50)
“I know we’ve been talking about blockchain for years. Gartner put it on the data and analytics time cycle in 2019 as this rocket ship that is going up and then two years later, it fizzles and it’s gone. But I am bullish on blockchain in the service of data management and how business is run. It is coming. It’s slow and business adoption is lagging, but there’s something there. Is it going to solve all problems? Of course not…but there are some problems that are purpose-built for blockchain in the data management realm that, I think, are going to be very interesting, particularly when you fold in the notion of widespread data sharing. Blockchain is very good at creating ecosystems of shared data.” — Malcolm Hawker
Malcolm’s Professional Epiphany (24:45)
“I can vividly remember…when I was moving up the corporate ladder. I’d been getting slow and gradual raises. Interestingly, I was bound to one company during my process of getting a green card in the U.S.…what I figured out was that I had an epiphany that was professional and personal, which was that I’m in charge. I am in charge. Hard stop. Period. There is nothing being done to me. I cannot blame this person or this person…or this situation for things that are happening to me. Everything that happens to me is a direct result of conscious or unconscious actions.” — Malcolm Hawker
Essential Leadership Qualities (1:01:25)
“Inspire. I want to inspire people. That’s definitely one. I will say I am a hands-off leader. I hate being micro-managed which means that I am constitutionally required to be hands-off in my leadership style. And let’s say supportive. I think that a lot of that has to do with setting clear expectations. That is the kind of support that I need. To me, as a very hands-off person, as a very self-driven person, as a very self-motivated person, just tell me what my boundaries are. Tell me my budget. Tell me my timeline. Tell me my constraints. Tell me your expectations of me. To me, that is the ultimate form of support…that is how I try to manage as a leader.” — Malcolm Hawker
About Samir SharmaSamir Sharma is the CEO and Founder of datazuum, a data strategy, and analytics consulting firm. Advising businesses on how to prioritize data activities, identifying growth possibilities and using data to boost revenue and profit. His clients span the UK, Europe and North America while ranging from medium-sized firms to major multi-national corporations. Prior to datazuum, Samir worked at Computer Sciences Corporation, Accenture, Christie’s and Vertex Business Services where he led the development of their data and analytics business. He writes on all things related to data strategy, roadmap development and how to execute the data strategy where he shares his experiences and lessons learned. He is a frequent keynote speaker and hosts the Data Strategy Show podcast, which was named one of the Top 10 Podcasts of 2022, as well as leading Ask Me Anything events with top data executives.
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Samir Sharma on LinkedIn
Visit datazuum’s website
Listen to the Data Strategy Show podcast
What happens when you get two modern data experts in a room to talk shop over a beer? Let’s find out!
In celebration of the 20th episode of the podcast, Malcolm sits down again with the guest who kicked things off on Episode 1 of the CDO Matters podcast, Scott Taylor (aka. The Data Whisperer). Malcolm hosted Scott for a casual chat in his Florida home to catch up and talk all things data over drinks. Throughout the episode, the two discuss current trends, issues and observations about the data space.
Topics of conversation include:
•A retrospective of the CDO Matters podcast
•Data storytelling and finding a unique voice within the industry
•Lessons and tips for current and aspiring CDOs
•The importance of data messaging
•Upcoming events and appearances
And so much more!
Key Moments[3:00] Looking Back at Episode 1 on Data Storytelling
[10:00] Bringing a Unique Voice to the Data Conversation
[15:30] The Failure in Data Management Consulting Today
[23:12] Lessons for CDOs from Scott and Malcolm’s Travel Consulting
[28:05] Reformatting Data Message Delivery
[31:15] Misconceptions about Organizational ‘Culture Change’
[35:50] Separating Data from Analytics: Analytical vs. Operational
[41:06] Scott’s Upcoming Data Plans and Appearances
Key Takeaways Delivering a Data Narrative in a Unique Voice (10:00)
“I hope I am bringing a unique voice to the [data] space. That was the whole goal [with the podcast]. One of the reasons why I wanted Scott to be guest number one and why I’m thrilled that he’s guest number 20…I wanted this to be a different voice. I’ve been in the data space for a long time. A lot of what I see…is the same old messaging over and over and over…the conclusion that I came to is that the way we’re delivering the message is wrong…what I was seeing from Scott was him delivering the message in a very different way through storytelling.” — Malcolm Hawker
Separating Data and Analytics: Operational vs. Analytical Use Cases (38:20)
“Going back to analytical versus operational, I don’t know how you throw those into siloes. It doesn’t make any sense to me. What I see happen is when you give the keys to domains or groups or functions or departments to come up with their own analytics…they’ll create their own rules and their own data definitions and their own data quality rules and dashboards…and maybe that freedom is good, but then you have to operate cross-functionally to move a contract out of sales and into finance or move the product from manufacturing into marketing…and then, what happens?” — Malcolm Hawker
Selling Leadership on a Data Solution (31:20)
“When you’re going for funding [on a data project] and you’re back at saying that some version of this latest, greatest thing is going to fix all of the problems that I told you we were going to fix…the same as the last time. And so you’ve got, I believe on the business side, a certain amount of cynicism and weariness…And I don’t think it helps that, as data people, we come barging in there talking with selective amnesia…pretending that we never said that our previous approach would solve the problem.” — Scott Taylor
About Scott TaylorScott Taylor, also known as The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of master data and proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” At MetaMeta Consulting he works with Enterprise Data Leadership teams and Innovative Tech Brands to tell their data story.
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Scott Taylor on LinkedIn
Visit MetaMeta Consulting’s website
Episode Overview There’s a well-known saying: “Teamwork makes the dream work.” Despite there being some truth behind that, the dream can’t become a reality without the right team.
This is especially true when recruiting and staffing skilled professionals for your enterprise’s data organization.
In this episode, Malcolm interviews Kyle Winterbottom, the CEO of Orbition, a niche talent consultancy helping organizations staff data and analytics roles across the globe. Running a company solely focused on helping companies build, grow and optimize their data organizations by recruiting top-tier talent gives Kyle a unique perspective on the market for data-centric roles. As such, this episode of CDO Matters is a great resource for data leaders working to build out a data and analytics function, or perhaps even become a chief data officer (CDO) themselves.
When discussing the current state of the market specifically for CDO talent, Kyle notes that there’s a massive gap between the number of companies hiring CDO-level roles and the total number of possible applicants — a reverse of the supply and demand in the job market for data engineers.
So, not only is there a scarcity of CDO roles, but Kyle also notes that many companies actually struggle to define exactly what the CDO role should entail — where many still focus on Python skills and other technical proficiencies typically not required by senior executives. This is leading to a number of suboptimal hires, where the scarcity of roles is often filled by people poorly suited to meet the expectations of a senior business leader.
Establishing a track record of the delivery of tangible business outcomes is how Kyle recommends data leaders highlight their resumes should they seek these scarce CDO positions since ultimately, it’s those business results that companies expect from their head of data.
In stark contrast to leadership roles, he notes an abundance of unfilled technical roles in data organizations — particularly data engineers. Kyle notes that if you want to earn the same amount of money that data scientists were pulling in five years ago, now is the time to become a data engineer. This demand for technical skills is also being seen in data governance-related roles — where years of companies focused on “shiny objects” in the data space has led to a degree of talent debt in the areas of data management fundamentals — including governance.
When discussing what it takes to retain and develop data-related talent, Kyle notes that fundamental shifts have occurred since the global pandemic — where in the past, data practitioners were primarily asking themselves three things:
- How much will you pay me?
- Will the brand name look good on my resume?
- What kind of tech will I get to play with?
However, in recent years, these needs have shifted. Increasing amounts of data talent are looking for their work to be valuable, visible and impactful.
When providing his insights on landing a CDO position, Kyle stresses to “not chase a title,” but instead chase positions with roles and responsibilities that tightly align to the typical responsibilities of a CDO — even if a company may not call it that. Kyle correctly notes, “If you want to sit at the top table, then [the delivery of value] is the job…despite that most organizations still advertise for python skills in a CDO.”
When discussing the issue of short CDO tenures, Kyles likens the current environment for CDOs to that of professional sports coaches and general managers of highly elite teams — where if you are a new hire, but you aren’t able to show some quick wins in a relatively short period of time, your position as CDO will likely be on the chopping block.
Key Moments [1:05] Recruiting and Retaining Qualified Data Talent
[4:32] The Current State of the Data Market
[7:20] Leadership Roles Vs. Technical Roles
[9:35] The Decline of Data Science
[12:00] Increased Demand for Data Engineering
[17:34] Proposing a Data Strategy
[20:41] Data Leadership Trends in 2023
[23:20] Treating Data as a Product
[26:30] The Produce Management Lense
[30:02] Professional Advice for CDOs
[32:50] CDO vs. CDAO
[36:30] CDO Tenure Expectations
[39:00] Incentivizing Data & Analytics Leaders
Key Takeaways Recruiting Data Talent vs. Leadership Talent (7:30)
“If there is a senior data engineering role, it might get a handful of applicants, if that, over a period of two to three months. If there is a leadership role [Director, VP, CDO type role], that will get hundreds of applicants in a number of minutes.” — Kyle Winterbottom
Increased Demand for Data Engineering (10:51)
“The marketplace [for data engineering] is in the same place data science was five years ago, where people are getting stupid uplifts in terms of salary, stupid uplifts in terms of title…just because the number of people out there that can do that job is so few and far between.” — Kyle Winterbottom
Changing Interests in the Data Space (14:40)
“I think there has been a dramatic change from even five years ago…most data and analytics practitioners were interested in: How much will you pay me, will the brand name look good on my resume and what kind of tech will I get to play with. These were the top three factors…but their wants, needs and desires have changed.” — Kyle Winterbottom
The Current State of the Data Leadership Market (21:10)
“I think the data leadership market will have its data again — for me, it’s just a matter of when, and if that will be 2023, or maybe just a little bit beyond…and I say that because the instability in that market at the moment is so huge that I think a lot of hiring decisions are being made wrongly.” — Malcolm Hawker
About Kyle Winterbottom Kyle is the Founder and CEO of Orbition, a data and analytics talent consultancy located in London and New York responsible for staffing major organizations around the globe. Since 2020, they have served as a dedicated, full-service talent solutions provider for the industry. He is hugely passionate about enabling organizations to drive decisions and obtain value3 from the use of data, analytics and AI. Kyle firmly believes that the two biggest assets that a business has are people and data.
EPISODE LINKS & RESOURCES: Follow Malcolm Hawker on LinkedIn
Follow Kyle Winterbottom on LinkedIn
Visit Orbition’s website
As an expert in your field, you need to approach your work from every perspective.
If a medical doctor can deliver a particular diagnosis for a patient, then they should also be able to do the same for themself. The same principle applies to data organizations and how they approach their own enterprise data.
As a CDO, if your internal customers must pay to access the data or insights you provide, would they feel confident in your ability to deliver value from your data products? Is your business singularly focused on understanding and meeting customer needs — both now and on the road ahead?
If not, then what’s standing in your way? For many CDOs, the answer lies in making that crucial transition from being data-driven to data product-driven.
In this episode, we discuss making the shift to becoming data product-driven. Malcolm is joined by Saleem Khan, Discovery Data’s Chief Data & Analytics Officer (CDAO). During the discussion, Saleem shares valuable insights on thriving within the CDO’s function for an organization whose core product is data.
Saleem’s shared insights include a framework for managing a data product pipeline, leading a team of data product managers, and implementing processes to anticipate future market demand. Saleem’s recommendations even include insights on a sales enablement methodology that can be used to ensure data consumers will derive benefit from data products and the critical role that a marketing function can play in ensuring data customers have a clear understanding of how a data product helps deliver a specific business outcome.
Given Saleem’s role is primarily as a Chief Product Officer (CPO), it should be no surprise that he won’t discuss data quality, data governance, data pipelines or anything else deeply focused on data management. Instead, he focuses on several best practices and actionable insights for how to approach the role of a CDO should you wish to ensure stakeholder value remains at the core of everything you do.
Key Moments[1:57] Saleem’s Career Journey to Discovery Data
[3:45] How Data Can Be Monetized/Validated
[6:30] RAD Defined
[9:12] The Role of a CDAO
[13:10] Implementing the FRAME Framework
[19:30] Aggregating Customer Data
[21:40] Data Governance as a Business Model
[23:35] Anticipating Consumer Interests
[25:20] Taking a Product Management Approach
[27:25] The Problem with ‘Data Literacy’
[31:24] The Current State of Blockchain
[34:00] Data as a Consumerized Product
[38:51] The Fragmentation of Data Sharing
Key Takeaways Predicting Debt and Data Monetization (3:45)
“One of the first forays I truly had into data science and the data world was building out a prediction model…where we would try to determine which companies were most likely to issue debt. So, on one end of the spectrum, you’ve got Microsoft and Apple which are incredibly cash-rich and they usually don’t borrow…then on the other end of the spectrum, you’ve got companies that require a lot of cash because they’re very capitol-driven and capitol-intensive and have to take out a lot of debt. And whenever debt is taken out, SMP has to take a rating on it.” — Saleem Khan
The Role of a CDAO (9:14)
“As Chief Data and Analytics Officer, 50% of my job is sales and marketing, the other 50% is product development…My job becomes making sure I communicate with customers, especially our largest customers, as often as I can…Data is our product, so [for customers] who better to hear from than the Chief Data Officer about what trends there are, and where you are taking your data set?” — Saleem Khan
Adopting the FRAME Framework (14:12)
“We have a framework as part of our data operations. We have another framework called, FRAME. FRAME is an acronym that stands for ‘Fuel, Refine, Analyze, Magnify and Execute’. Each of these components is a different part of the data operations lifecycle…There are multiple ways to distribute your data and your content to customers.” — Saleem Khan
The Problem with Data Literacy (27:25)
“I happen to be vehemently opposed to that phrase [data literacy] because it turns the problem to a user problem where I think it should be on the creation side. If you’re creating a data product, if you’re creating something for consumption…and they don’t know how to use it and don’t know how to derive value from it, I would argue that that is a product failure, not a user failure.” — Malcolm Hawker
Creating a Product Narrative (29:25)
“When you have a product that has a miss, there is one of two reasons: One could be that it was just a terrible product, and two could be ‘wrong place, wrong time’…but the products that do work out, they tend to work out because the CDO is working directly in tandem with sales and marketing to create that narrative, to tell that story of value to the customer… to make sure that customer has a simple and crystal clear understanding of how this data product will deliver a specific business outcome.” — Saleem Khan
About Saleem KhanSaleem is the Chief Data & Analytics Officer (CDAO) at Discovery Data. With over 15 years of experience in the data space as a patented product, data and technology executive, he remains proficient at using data-driven and analytical techniques to deliver new digital products and implement digitally-enhanced process transformations.
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Saleem Khan on LinkedIn
Visit Discovery Data’s website
When it’s time to make a big decision, it’s always great to get a second opinion!
This is especially true when a major business decision comes your way. When it comes to something as foundational for your business as your enterprise data, it’s best to consult the experts. Growing your business starts with an effective data strategy. But what if you could bring your burning data questions to a seasoned professional without the financial burden? There’s nothing better than hearing advice and insights from a leader in the field.
Host Malcolm Hawker does just that kicking off his inaugural monthly session of CDO Matters LIVE. In this special live episode, he answers top-of-mind inquiries about all things master data management (MDM), data governance, data fabrics, business value and more.
Joined by Profisee’s Director of Digital Marketing, Ben Bourgeois, Malcolm opens the episode by posing the question, “Why do we separate analytical [reporting] uses of data from operational [data management] uses of data?” Data and analytics are often used in the same sentence but treated as two separate items.
He immediately points out the relation between the two with analytics often leading to operationalized insights and decision-making which ultimately leads to action within a business. While separating them provides freedom on the analytical side, it often leads to analysts then defining their own business rules, data definitions and how they want the data to be shown in future reports. This further isolates the two areas from being used cross-functionally across multiple departments for individual purposes.
Ben then poses the question of whether this separation stems from data ownership within an organization. Malcolm clarifies the ideal definition of data ownership by explaining how it refers to data laws, rules and standards within a business that are applied cross-functionally. The other aspect of ownership then relates to enforcing those established policies. Ultimately, he concludes that assigning individual owners only hurts rather than helps a data-driven enterprise.
From there, Ben provides Malcolm with some of the more notable and relevant topics and inquiries hitting the data space as of late. The topics discussed throughout the remainder of the episode include:
- Transitioning from top-down or enterprise-wide initiatives to more federated approaches focused on business units
- The value of treating data as a product
- Effective marketing and the difference it makes for a master data management (MDM) or IT initiative
- Using Salesforce and other CRMs as a substitute for MDM within an organization
…and various questions submitted during the live Q&A!
If you want to ask your burning data questions live with Ben and Malcolm, be sure to register for the next of our live monthly sessions of CDO Matters LIVE.
EPISODE LINKS & RESOURCES:
Follow Malcolm Hawker on LinkedIn
Follow Ben Bourgeois on LinkedIn
Register for an upcoming session of CDO Matters LIVE
The truth isn’t always black and white. Sometimes, it requires more context and background when attributed to different scenarios and situations.
The same can be said about your data and whether a “single version of the truth” can be properly applied to multiple use cases for your business.
In this episode, Malcolm interviews Jeff Jonas, the Founder, and CEO of Senzing — a software company on the leading edge of developing “entity resolution” solutions — which solve the growing challenge of uniquely identifying people or objects across multiple systems of duplicate, low-quality data. Malcolm and Jeff discuss how advances in technology are fueling more modern forms of entity resolution, where companies are now able to implement more context-centric approaches to complex matching, particularly within their master data management (MDM) programs.
As technical as “entity resolution” may sound, the two uncover the global effect this technology has on people each day — including the job of the Chief Data Officer (CDO). Also known as “disambiguation” or “fuzzy matching,” effective entity resolution allows software systems or data stewards to decipher whether records for Richard Smith and Dick Smith may represent the same person, even when it is not overtly suggested by the data.
Jeff describes how entity resolution sits as a foundational component of data within MDM, customer relationship management (CRM), know your customer (KYC), supply chain and every other major business process that relies on accurate, trustworthy data.
Jeff correctly notes that aside from horrible customer experiences that may arise from a lack of effective entity resolution, “it creates a lot of waste for companies to think you are two or three people instead of one.” Citing a person’s example of having their name represented three distinct times in a hotel loyalty club database, he emphasizes the toxicity that comes with a lack of focus on entity resolution for companies who are trying to be both customer and data-centric.
While many companies — particularly those already investing in AI/ML — may be attracted to implementing DIY solutions for entity resolution, Jeff notes that it’s “super expensive to build”, especially given the complexity and diversity of data, and even language itself. The ability to understand meaning across objects, cultures, languages and even alphabets is at the core of reliable entity resolution and building bespoke solutions for tackling these complex problems — at scale — is beyond the capabilities or budgets of an overwhelming number of companies.
When considering a “single version of the truth”, Malcolm unpacks the 30-year history of large, monolithic enterprise resource planning (ERP) suites that created the mindset of master data only living in a singular place within the organization. Thanks to the democratization of IT, the “single version” mindset is shifting both as a practicality and as a business need. Today, master data can be sourced from a single location while supporting multiple versions of truth based on the use case of that data.
In talking about the evolution of large-scale entity resolution, its use in MDM to enable multiple versions of the truth and the legacy requirement to have data stewards manually review records, Jeff notes, “There are definitely times…when you want a human to take a look and make an adjudication. But, I will tell you, in large-scale systems, you don’t have enough humans.”
Rather than adding more people into data stewardship roles to support higher confidence matching, Jeff advocates the approach of widening the pool of data used by entity resolution processes — beyond just name and address — to make match decisions, including the possible use of third-party data sources.
The last few minutes of the conversation go deep into AI/ML, and how these new technologies are used to augment human data stewardship processes. Jeff makes a great case to suggest that most stewardship tasks could be mostly automated, but that many companies are unable to duplicate pure human judgment.
Throughout the conversation, Jeff and Malcolm take extremely complex technical issues and make them digestible and relatable to CDOs — consistently refocusing on how using entity resolution is critical to establish truth in an organization, especially when using MDM systems to manage said truth. CDOs who want to have more informed conversations with their technical staff about the role of entity resolution going beyond just “fuzzy matching” will find this episode of CDO Matters highly insightful.
Key Moments[3:42] Entity Resolution Defined
[7:50] The Impact of Poor Data Quality
[11:23] The Death of the ‘Single Version of the Truth’
[15:45] Entity Resolution Failures
[24:03] Understanding Unique Entities
[26:13] The Cost of Being Wrong
[29:10] Human Intervention vs. Trust in the Algorithm
[32:05] Gaining New Insights with MDM
[35:09] Valuing Human Judgment
[40:03] The Future of Entity Resolution in Digital Transformation
Key Takeaways What Is Entity Resolution? (1:58)
“Entity resolution is recognizing when two things are the same…it’s [also] called ‘fuzzy record matching’, ‘link detection’, ‘disambiguation’, ‘match/merge’ and lots of names. It’s been congealing into this term ‘entity resolution’ and is being more used. And really, the definition that I would have for it is recognizing when two identities are the same despite being described as different.” — Jeff Jonas
The Cost and Complexity of Efficient Entity Resolution (5:15)
“This problem [with poor entity resolution] is ubiquitous, and it turns out, is super expensive to build. People think you can hire a little team and do some AI/ML and think you are going to match well. And I am telling you, you cannot create something competitive in five years for twenty million.” — Jeff Jonas
Is the ‘Single Version of the Truth’ Dead in 2023? (13:07)
“There are still many people saying you need a single version of the truth…At an operational level [within a company], there are multiple versions of the truth. The way a marketer would define a customer is different than the way somebody in finance may define a customer, particularly B2B, where one would be a ‘sell to’ and the other is a ‘bill to,’ and they are both correct. A lot of people still think that is what MDM is, and it can be that if you want it to be that, but it doesn’t have to be.” — Malcolm Hawker
Working with Multiple Versions of the Truth (14:12)
“I think the ‘single version of the truth’…those are the dark ages, the dark days. The truth is you really want systems that can present truth to the eye of the beholder. It’s about who the recipient is. But there are two forms of truth: One is about separating ‘who is who?’ from which attribute is the best attribute…and how many entities does the organization have? Do you really want marketing to have a different [data] account than finance?” — Jeff Jonas
Human vs. Software: The Role of Human Judgment (29:38)
“There are definitely times/cases in data when you want a human to take a look and make an adjudication. But I will tell you, in large-scale systems, you don’t have enough humans. Second, I will tell you, ‘How does the human do it?’ The human is using additional data. It’s either data stuck in their head or they’re searching it up somewhere…but a lot of times, you have to actually do research…so making these decisions on records with some human intervention is about adding data. And one of the things that we propose is that there are kinds of data that is the initial data needed.” — Jeff Jonas
About Jeff JonasJeff Jonas is not only the CEO and Founder of Senzing but also the Chief Scientist. Since 2016, the organization has provided fast and easy API for accurate data matching. For more than 30 years in the field, he has been at the forefront of solving big data problems for both companies and governments. National Geographic recognized Jeff for his talents in the data space, referring to him as the “Wizard of Big Data.”
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Follow Jeff Jonas on LinkedIn
Visit Senzing’s website
Learn more about ‘entity resolution’
View a PDF of Jeff’s publication, Privacy by Design in the Age of Big Data
For CDOs to be successful today, they need to think more like a product manager.
After all, product managers are responsible for every facet of their product. They determine which customer needs their products fulfill and define what success looks like for their product. And they’re ultimately responsible for reporting that performance to executive leadership.
Hopefully those responsibilities sound familiar to listeners of the CDO Matters Podcast — except that for them, their core product is data.
In our latest episode, Malcolm is interviewed by Rishabh Dhingra on the Inspired Podcast, where Malcolm shares his perspectives on the growing trend toward treating data as a product. CDOs who are considering the addition of the product management mindset into their business will find his perspectives refreshing — given the great value that he believes product managers, and treating data as a product, can bring to most data-driven organizations.
Malcolm shares details on his expertise in the field of product management, having been a Product Manager, a Product Director and, ultimately, a Chief Product Officer (CPO). Having managed teams of product managers in several software companies through the heyday of the internet boom, Malcolm has first-hand experience working in highly agile and fast-paced environments — where quickly adapting to changing needs was a daily struggle.
As Malcolm describes it, the core DNA of a good product manager is all about problem-solving — where professional product managers are trained specifically to determine the optimal combination of product attributes to address customer needs given known constraints on time, money or resources. Product managers also know how to build business cases to support investments in their products; otherwise, businesses wouldn’t invest in them.
One of the biggest benefits of implementing more product management into data management is that they will provide the skills necessary to build business cases for data and analytics products — being a standard operating procedure in the world of product development.
When it comes to data as a product, Malcolm believes many data leaders are often missing the mark by incorrectly focusing efforts on defining products rather than customer needs. He explains that it ultimately doesn’t matter if a data product is a field, an attribute or an entire table — but what matters is if a customer need is solved.
The need for data people to take a “bottoms-up” approach to data products — where the product is a function of the available “raw materials” — is a major flaw in data organizations that product managers could help a CDO avoid since product managers are inherently focused on solving customer needs.
Why should companies consider managing data as a product? According to Malcolm, companies that deeply integrate product management practices into the field of data management — and who deeply embrace all aspects of data as a product — will drive competitive differentiation.
The benefits of integrating product management practices into data management are many, but his highlights include better business cases, resource prioritization, cost management and many others as just a small subset of the universe of benefits with more focus on data as a product.
By the end of this episode, current or aspiring CDOs who have not already considered the integration of product management practices into their data organizations — both for products and the supporting organization — should have a roadmap for implementing these PM practices into their data organization.
Key Moments [1:15] Transitioning from Product Management into Data and Analytics
[7:06] Resolving Customer Problems with Customer Data
[12:30] Malcolm’s Role at Profisee
[15:40] Confusing Data Migration and Warehousing with Data Management
[19:20] MDM Implementation: Successes and Fails
[27:30] Why Product Managers Make Great Business Leaders
[29:40] Defining Data as a Product (DaaP)
[37:20] Applying Data as a Product Within Your Organization
[47:30] The Future of Data and Analytics
Key Takeaways Malcolm’s Role as a Thought Leader and MDM Evangelist (12:40)
“Primarily, I’m focused on evangelism…it is my job to raise the awareness in the market of the importance of data and analytics, the importance of master data management (MDM). How MDM can drive value for organizations and how it can be used as a foundational element for digital transformation.” — Malcolm Hawker
Data Warehousing vs. Data Management/Governance (15:40)
“So many companies that if you just put all of the data in one place that you have solved for data quality. That you’ve solved for having a single source of truth. That you have solved for having consistent data governance. That couldn’t be farther from the truth. All you’ve done is put your data into one bucket. You may have limited the number of queries that you have to make or the number of sources that you have to go into. You may have made it a little easier to centralize permissions and access to that data…but putting it into one place doesn’t solve for that issue…I am all for using data warehouses and I am all for using cloud-based solutions for housing data, but if you don’t address some data quality issues, you’re going to have a lot of problems.” — Malcolm Hawker
Limiting Your Scope (23:45)
“Most data and analytics leaders are not building business cases. That means they struggle with scope. But product managers know you’ve only got time, people and money. If one of those has to go, then you have to limit your scope…If you don’t have a business case, then it’s really hard for you to limit your scope. It’s really hard for you to prioritize. It’s really hard for you to understand where the biggest benefits are going to be…you can’t differentiate whether A or B or C is going to drive value for the business. It inevitably leads to scope creep. It inevitably leads to situations where data and analytics leaders can’t justify the things that they’re doing.” — Malcolm Hawker
Bringing Product Management to the Data Space (33:42)
“If we could apply more product management into data management, data management would be a much better place. I would argue it would be far more customer-centric, it would be far more effective, it would be far more productive, we would be able to quantify the business benefits that we were driving, we would be able to prioritize our efforts, we would be able to spend money more efficiently, but what we do instead is we get into these arguments about, ‘What is a data product?’ Is it a field? Is it an attribute? And it’s not helping, because it’s backward. Start from the need.” — Malcolm Hawker
Where are Data and Analytics Headed? (47:35)
“In terms of the future, there are some things that we know are here and will continue to be here and continue to expand [into] what I would have called when I was at Gartner, augmented data management. What that means are the application of AI and [machine learning] and cool new technologies…to provide added layers of automation in the world of data management. I would put the creation of management of data fabrics in the bucket as well…with limited numbers of people, we need more and more automation in the data space.” — Malcolm Hawker
About Rishabh Dhingra Rishabh Dhingra is the host of the Inspired podcast and is currently a Solutions Consultant in Business Analytics at Google. Having graduated from the Thapar Institute of Engineering & Technology in 2011, he serves as a veteran in the field with more than 11 years of experience architecting, designing and developing enterprise-scale business intelligence and analytics solutions for insurance, legal, banking and other industries.
EPISODE LINKS & RESOURCES: Follow Malcolm Hawker on LinkedIn
Check out the Inspired podcast
Follow Rishabh Dhingra on LinkedIn
First impressions are everything.
As a brand-new CDO, it is important to hit the ground running with a data strategy that pinpoints key use cases and quickly delivers value within an organization.
In our 14th episode, Malcolm shares his perspectives on the top deliverable for most CDOs: the definition and execution of a corporate data strategy. He outlines his model for a ‘Data Strategy Minimum Viable Product’ (MVP), which embraces a highly iterative and pragmatic approach to defining and executing a strategy. This approach starkly contrasts more traditional approaches which often take years to deliver any business value.
Rather than separating a strategy’s definition from its execution, the Data Strategy MVP deeply interconnects the execution with the ongoing evolution of the data strategy — where CDOs can earn the right to change corporate cultures or operating models by delivering business value rather than management edict.
Malcolm argues that forcing a business to wait years — or even several months before it will realize any benefits of a data strategy — is a key reason for shortened CDO tenures.
While a typical approach to a data strategy would involve 6-12 months of business analyses and requirements gathered across an entire enterprise before actually executing a strategy, the Data Strategy MVP hinges on a razor-sharp focus on quickly identifying a few key business outcomes.
This is quickly followed by the definition and execution of a data strategy specifically to address those limited sets of outcomes. By repeatedly focusing on a small set of outcomes, organizations can successfully execute a holistic data strategy.
Malcolm also dives into how taking a more tactical and results-driven approach to implementing a data strategy requires a strong data leader who can balance longer-term needs — such as defining an adaptable technology architecture or the right governance model — against short-term needs.
Finding this balance will not be easy but is necessary to ensure short-term decisions do not compromise the ability to fully align the data to the business strategy in the long haul.
Another key to the Data Strategy MVP — as outlined in the shared model — is the acknowledgment of the several business characteristics that CDOs cannot change in the short term. These include the data culture, corporate operating models and overall data and analytics maturity level.
While more traditional strategy approaches would place changes to these things as strategic dependencies, Malcolm instead argues they should be considered more as constraints. This helps guide decisions on the best business outcomes the evolving strategy should be focused on in the immediate future.
CDOs who have been tasked to execute a data strategy should find this episode of CDO Matters highly useful — especially those concerned that too much of a focus on data strategy is hampering their ability to deliver value.
Newer CDOs unfamiliar with more agile approaches to program management will also benefit from this episode — as will those aspiring CDOs who are looking to make an impact for their business partners by finding ways to bring value in more iterative ways.
Key Moments[2:10] Why Are CDO Tenures So Short-lived?
[4:12] The Responsibilities of the Modern CDO when Establishing a Data Strategy
[7:02] Creating a Centralized Data Culture
[13:05] MVP Data Strategy Attributes
[18:45] Defining Your Outcomes
[20:52] Filling Gaps in Governance Maturity
[24:30] Leveraging Analytical Insights Rather Than Operational
[28:15] Delivering Realistic Business Outcomes
[30:40] Succeeding as a CDO
[33:05] Establishing an Analysis Roadmap and Governance Framework
[36:46] Placing Technology at the End of Your Strategy
[42:10] Summarizing How to Provide Significant Value
Key Takeaways Why are CDO Tenures so Short-lived? (10:32)
“I would argue that one of the reasons for very, very, short CDO tenures is that [CDOs] rightfully identify that some fundamental ways the business operates need to change… however when you put those organizational changes or those cultural changes or those operating model changes as dependencies to be able to deliver value — and if you make those changes your top priority — you are going to have a hard time delivering value in the short term.” — Malcolm Hawker
Start Small and Grow from There (18:32)
“A key to this whole thing — being MVP-driven — is to focus on a limited number of outcomes... not all of them — one or two. If you want to take an MVP approach to a strategy — and I would argue it’s the best thing you can do is to show some quick wins and show some value and not get stuck in an 18-month long discovery and consulting engagement.” — Malcolm Hawker
Delivering Plausible Value (32:25)
“If you want to succeed at a data strategy…you do need to incorporate some idea of executing against the strategy as a part of your strategic model, where you plan to deliver iteratively as a part of executing on that strategy. Where that strategy evolves based on your ability to deliver.” — Malcolm Hawker
Limit Your Scope and Don’t Boil the Ocean (36:14)
“For now, you just need to figure out the governance needed to enable [your top outcome]. It’s simple, stay focused, keep a limited scope, be agile, deliver on one outcome. Figure out the governance dependencies for that one outcome instead of figuring out the governance dependencies for everything. Because if you try to figure out the governance dependencies for everything, you’ll be at it every day for the next three years — two to three years easily. That will consume every resource you’ve got, you won’t have delivered value, and it’s not going to be good. It’s not.” — Malcolm Hawker
EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedIn
Chief Data Officers don’t stay in their roles long. Here’s why.
Why Do Chief Data Officers Have Such Short Tenures?
Curiosity can lead you to unlikely places. For Malcolm Hawker, a simple curiosity about enterprise data led to a lasting career as an expert in the field and a thought leadership figure in the data and analytics space.
Malcolm is interviewed by Anthony Algmin on the Data Leadership Lessons podcast to discuss his personal journey to becoming a thought leader in the data field. In this lively conversation, he shares insights on his career progression starting as a phone-based Technical Support agent for AOL in the mid ‘90s making $7 an hour to where he is today. Along the way, Malcolm shares several valuable insights on the current state of data leadership with practical advice on how CDOs can leverage critical data to become a more data-driven organization.
Malcolm dives into why he chose to leave his position as a Gartner Analyst and use podcasts, LinkedIn and other channels to share best practices with CDOs as a part of his mission to “raise the bar” on data leadership. A common thread across Malcolm’s interview is the idea that many of the best practices consistently shared with CDOs and other data leaders are not being implemented today. He attributes much of this as a failure to align business incentives with IT incentives, as well as a failure by CDOs with more of an IT background being unwilling to defer to other experts to help solve difficult problems — at least those who aren’t high-priced consultants.
Through this 45-minute conversation, Malcolm’s passion for helping CDOs consistently sits at the core with the support of his deep experience as a consultant, a software vendor, a CIO and a Gartner analyst. He explores the importance of CDOs having the right combination of business, technical and sales skills — and the importance of using the right messaging and mediums to ensure data organizations place business first, not technology.
CDOs looking for new — and perhaps a bit irreverent — views on the state of data leadership today should find this episode of CDO Matters a breath of fresh air.
Key Moments [1:00] Malcolm’s Career Overview in the Data Space * [6:30] The Early Internet Days with AOL * [9:20] Pursuing Data Management * [14:40] Adding Value as a Data Thought Leader * [15:43] The Appeal of Data Evangelism * [25:20] Practicing Humility as a Modern CDO * [31:50] Making Data Literacy Actionable * [36:15] The Buzz Behind Data Fabric and Data Mesh * [39:10]* Learning from Data Mistakes
Key TakeawaysWearing Multiple Hats in the Data Space (5:02)
“In many ways, I learned the wrong way in some instances. Or the less effective way, I should say, of doing MDM and data management and implementing a governance program. But those lessons really carried forward and through the rest of my career…I’m in a unique position of having seen what works both as a practitioner and an analyst and a consultant and a software vendor. So, I’ve worn every hat. — Malcolm Hawker
Malcolm’s Endgame for Data Thought Leadership (10:42)
“After 30 years of having been in this space, I feel like I know what works, and I know what doesn’t work. I’ve seen it work, and I have seen it fail. I’ve been on the end of the failures, so I really want to help people avoid that stuff. I want to help CDOs succeed. I want to help VPs of Data and Analytics succeed. I want to extend the tenures of CDOs. I’m in the right place. I feel like it is the right time.” — Malcolm Hawker
The Makings of an Effective CDO (28:25)
“It’s a bit of a unicorn skillset. The right CDO is certainly a bit of a unicorn. It’s half sales, half business and half technology — and yes, that’s three halves. So, it’s tough, but there are people out there that do it.” — Malcolm Hawker
The Truth about Data Literacy (32:08)
“I was at a presentation…and they were talking about data literacy and I asked him a question that I thought just was a mic drop. I said, ‘If data leaders were more business literate, would we be asking business leaders to be more data literate?’…I tend to have a little bit of a problem with the phrase ‘data literacy’ because I think it’s condescending because the flipside of that is illiteracy.” — Malcolm Hawker
About Anthony AlgminAnthony is the host and founder of Algmin Data Leadership and the Data Leadership Lessons podcast. He also serves as the Convergence Platform Program Lead at AbbVie, a pharmaceutical manufacturing firm based in Chicago. Anthony is also the author of the book, Data Leadership: Stop Talking About Data and Start Making an Impact!, published with DATAVERSITY. He has made over a hundred speaking appearances to deliver data leadership insights to the masses.
EPISODE LINKS & RESOURCES:* Follow Anthony Algmin on LinkedIn * Visit AbbVie’s website * Purchase Anthony’s book, Data Leadership: Stop Talking About Data and Start Making an Impact! * Visit the Data Leadership Lessons podcast
Do you have what it takes to be a Chief Data Officer (CDO) in today’s business landscape?
On the latest episode of the CDO Matters Podcast, Profisee Head of Data Strategy and former Gartner Analyst Malcolm interviews Justin Magruder, the CDO of SAIC Corporation. The conversation begins with a focus on his role as CDO as well as some of the major changes Justin has implemented within his organization to help SAIC become more data-driven.
This includes creating a data office center of excellence (COE) outside the IT organization that embraces a producer/consumer operating model — where it’s the job of the data office to provide data products that meet the needs of its consumers.
The data products — and core capabilities — are managed by a team of product managers within SAIC’s data office. Data serves as a primary focus where economies that efficiently share data are a top priority.
The discussion then pivots into Justin’s journey to becoming the CDO of one of the biggest technology services companies in the world. According to Justin, “For those who want to become a CDO, who aren’t already in technology, there is hope.”
In fact, Justin did not come from a background in technology, but rather as a Catering Service Manager at a large hotel in New York. Through a long series of choices always leading him back to data, Justin outlines a career focused on enabling companies to become more data-.
Data and analytics leaders who want to become a CDO — especially those without technology backgrounds — should be inspired by listening to this episode as Justin shares some of his keys to success. Justin stresses the importance of “communicating and collaborating” to anyone looking to transition into a CDO role.
Key Moments[1:25] The Role of the CDO in Modern Organizations
[5:37] Developing a Data Strategy
[9:42] Data Commonalities Across Industries
[12:03] Finding Purpose in Your Data
[14:46] Evangelizing as a CDO
[18:58] Treating Data Management as Product Management
[22:00] The Significance of Data Sharing
[25:02] Starting a CDO Career
[30:38] Important Characteristics of a Modern CDO
[35:20] The Importance of Communication for CDOs
Key Takeaways SAIC’s Approach to Managing Data (4:15)
“We help businesspeople get the data they need to do their job — it’s as simple as that. What makes us successful at SAIC is that we’ve been able to govern the intake of data requirements from across the business using very common ‘voice of business’ type approaches, very agile methodologies.” — Justin Magruder
Implementing a Successful Data Strategy (13:11)
“What [a data catalog] is really about, we have learned, is automation — and how we build a framework where we can have this integrated environment and we can really find out the authoritative source for any given data point at any point in time…so it’s really been rewarding to see how the introduction of data strategy to a technology firm is beginning to have a positive impact on how we do business with our customers and the value we provide to them.” — Justin Magruder
The Importance of Data Sharing (24:30)
“We realized we can really supercharge some of the work we are doing for our customers if we can do this kind of integration and sharing of information. It turns out we don’t need three copies of the same thing. If we can learn how to share one, it would save us all time and money.” — Justin Magruder
Becoming a CDO (25:50)
“For those people who aren’t already in technology, there is hope [for becoming a CDO]. I started my career after college with a big Fortune 500 company in a management training program, the company was Marriott. I went through Marriott’s management training program and became a Catering Service Manager. How did I get here?...I wound up in New York City for a big hotel...and I began to question how we put together profit/loss statements for my department. I worked with the hotel’s Food and Beverage Director to look at the way we were calculating gross margin and things like that...he said I should go to business school and go into banking. I came out of business school and fell into a technical role.” — Justin Magruder
About Justin MagruderJustin is the CDO of SAIC Corporation, a $7.4B Fortune 500 technology integrator at the forefront of enabling the digital transformation of some of the largest government entities in the U.S. He is a pioneer and a thought leader in the field of data governance, master and reference data and data operations, with more than 25 years supporting data operations, leaders and decision-makers to improve business performance through better data management.
EPISODE LINKS & RESOURCES:Follow Justin Magruder on LinkedIn
Visit SAIC’s website
Our understanding of data and its role within a business isn’t the same as it was 20 years ago. As data leaders embark on a modern data strategy, it is important continually adapt to change while operating with agility.
Malcolm interviews Samir Sharma, the CEO and Founder of datazuum, a data strategy and analytics consulting firm. Samir and Malcolm discuss many of the more significant challenges facing Chief Data Officers (CDOs) as they pursue their strategic priorities, with Samir providing a trove of useful and highly pragmatic guidance for any CDO looking to meet both short-term and longer-term goals.
Early in the discussion, they dive into the unhealthy fascination data leaders have on implementing technology without first understanding the business problems it will solve. Malcolm and Samir also share CDOs need to clearly understand their organizations’ existing operating model and their level of data and analytics maturity, as both are critical in defining a data strategy roadmap.
Samir shares his framework for working with CDOs whose stated strategic goals require greater maturity but are often starting at ground zero — which involves taking an agile and pragmatic approach to testing the organization’s ability to provide short-term business benefits around certain data use cases within specific engagement models.
The conversation then shifts to the importance of the culture of an organization and how that impacts the ability of a CDO to deliver a data strategy. However, unlike more conventional approaches to delivering a data strategy that puts culture change as a dependency for CDO success, Samir makes a compelling argument to work best within the existing culture and find ways to deliver value and speak in a common language without requiring drastic cultural shifts. He outlines how developing a common language and a clear understanding of expected outcomes is key for allowing CDOs to work within the cultural constraints of a given business.
Data literacy programs come under the crosshairs of both Samir and Malcolm, where it’s posited that data literacy programs may often be a symptom of larger organizational dysfunctions. Rather than seeing data literacy as the solution, Samir makes a case for a broader focus on having CDOs and their teams more focused on developing knowledge of business processes and where those processes are architected — all with a deep understanding of the importance of data from the ground-up.
CDOs focused on defining or executing their data strategies will find this episode of CDO Matters particularly useful, especially those frustrated with the speed or effectiveness of their efforts. This episode makes a compelling case for a more agile, iterative and pragmatic approach to a data strategy that removes major dependencies — such as culture change or a focus on literacy — to one focused on adapting to any existing culture and operating model.
Key Moments [2:06] Top Takeaways from Big Data London Conference & Exhibition
[7:28] Focusing on Business Outcomes and Building Data Technologies
[11:35] Creating a Data Strategy
[14:32] Data Ownership and Domain Retention
[19:10] Business Maturity and Understanding Data Products
[21:10] Assessing Your Data Strategy
[28:44] Remaining Pragmatic and Operating with Agility
[31:31] Maintaining a Business Culture and Preserving Data Values
[36:11] Knowing Your Business Process
[38:06] Deconstructing Data Literacy
[41:10] Breaking Down Your Business Data Model
[42:52] Making Changes to Drive Value
Key Takeaways Building Data Technologies (10:07)
“I think when I look at it, technology is easier than having to put together the notion of scratching your heads and wondering what you are going to do…I think this is just another iteration of the whole marketing movement for tooling…we had all of the various different terms that we were attempting to implement…all of those areas that which we’re trying to improve how we work, but why have we got all this stuff? Because the systems can’t integrate…we need to start with a data-focused view.” — Samir Sharma
Is Data Ownership Relevant? (14:31)
“I think it’s okay to talk about ownership from the perspective of an individual application. But when you start talking about domains that are used everywhere, it’s a horrible label…To me, the notion of ownership…not all data is created equally. I think the notion of ownership is misguided.” — Malcolm Hawker
Launching Your Data Strategy (21:48)
“There’s got to be a certain amount of standardization…a certain amount of proof of value that you can start to show stakeholders who are going to invest in this thing long-term. I think that’s one thing that many people forget. Before you go out and start thinking about centralization versus decentralization or a factory model or whatever you might want to have, you got to think about use cases…we want to prove value and we want to show how we can do it and want to show that early benefit to stakeholders.” — Samir Sharma
Promoting an Adaptable Data Culture (35:06)
“My view around culture is that there is one. We don’t need to disrupt it. What we need to do is get better at engaging with each other. We need to set a foundation of ways of working that will use business language and be able to talk to somebody about the outcomes that they are looking for.” — Samir Sharma
About Samir Sharma Samir is the CEO and Founder of datazuum, a data strategy, and analytics consulting firm. Advising businesses on how to prioritize data activities, identifying growth possibilities and using data to boost revenue and profit. His clients span the UK, Europe and North America while ranging from medium-sized firms to major multi-national corporations.
Prior to datazuum, Samir worked at Computer Sciences Corporation, Accenture, Christie’s and Vertex Business Services where he led the development of their data and analytics business. He writes on all things related to data strategy, roadmap development and how to execute the data strategy where he shares his experiences and lessons learned.
Samir is a frequent keynote speaker and hosts the Data Strategy Show podcast, which was named one of the Top 10 Podcasts of 2022, as well as leading Ask Me Anything events with top data executives.
EPISODE LINKS & RESOURCES: Follow Samir on LinkedIn
Listen to the Data Strategy Show podcast
Visit datazuum’s website
The world changed in March 2020. Public events and social gatherings took a backseat. As we recover from the pandemic over two years later, are we ready to attend large in-person conferences?
In this special 10th episode of CDO Matters, Malcolm becomes his own guest and takes a look into the future of in-person conferences through the lens of his experiences at four industry events this summer including an in-depth review of a celebrated annual conference, Microsoft Ignite.
Malcolm details the pros and cons of the conference. The highly anticipated event hosted 3,500 in-person attendees in Seattle, but over 200,000 online attendees around the globe. Most notably, the in-person attendees – many of whom came from overseas – paid thousands of dollars to attend while online attendees received free admission. Malcolm discusses the differences between the two experiences such as peer networking, vendor interactions, and expert advice. Was the in-person experience worth it?
He also discusses the incredible diversity of conference content – ranging from the desktop to the cloud and everything in between – being an additional challenge for CDOs seeking in-person networking and peer interactions. Unexpectedly, any data-related content that was available focused on data infrastructure, but not on people or processes supporting data management. The irony of a conference with little CDO-centric content or networking opportunities, but with a primary theme/track of “becoming data-driven” is highlighted in this episode. Here, Malcolm is forced to question the future of these events and whether in-person conferences remain relevant in 2022.
Despite a suboptimal experience in Seattle, Malcolm shares his firm belief that in-person conferences are still alive, and that creating a highly effective ‘hybrid’ event, based on experiences at other conferences he attended this summer – most notably the CDOIQ conference – is doable. There is a pent-up demand for conferences coming out of COVID-related lockdowns driving attendance, but more importantly at the right conference, there are still significant benefits CDOs can gain from in-person exchanges of insights and experiences that online events cannot provide.
Key Moments [2:07] The Role of the CDO and Why We Started the Podcast
[6:07] Audience Attendance
[8:52] Networking Challenges
[10:17] Presentation Style and Sensory Output
[12:37] Are In-Person Conferences Dead?
[14:02] The Future of Hybrid Events
[16:07] On-Site vs. Online Event Experience
[18:22] Discussions and Interaction
[20:07] Presentation Hubs and Breakout Sessions
[25:07] Conference Layout
[28:22] The Good and the Bad (What Worked and What Didn’t)
[34:27] Closing Statements
Key Takeaways Why the Podcast Started (1:33)
“We started this podcast because…what I saw in the market were really things that just weren’t working for CDOs…a lot of the same messages that we had been hearing for years. What I see less of is moving the needle: results. We know that CDO tenures are very short. Anywhere from two to two and a half years…when I look to the community of people, like myself, that are providing insights, providing best practices, providing the tips and tricks on how to be a better CDO, I saw very little derivation…yet businesses changed.” — Malcolm Hawker
Are In-Person Conferences Dead? (13:07)
“Are on-site, in-person events dead? Most certainly not. I went to four this year. I went to Ignite, the DGIQ conference in San Diego, the CDOIQ conference in Boston and I went to the Gartner Data and Analytics conference in September in Orlando and they were all full…there’s most certainly a demand for on-site events. Now whether this is a post-COVID phenomenon? I really don’t think so.” — Malcolm Hawker
In-Person vs. Online (16:07)
“Some people do actually enjoy interacting with vendors and being able to talk to others about their solutions. But if you don’t get the networking, if you don’t get to interact with vendors, if you don’t get the peer, one-to-one opportunities, then why would you attend in person? It would be really tough to justify spending thousands of dollars if you can do the exact same thing online”. — Malcolm Hawker
EPISODE LINKS & RESOURCES:Follow Malcolm on LinkedIn
Visit the Microsoft Ignite website
The data space isn’t what it was 20 years ago. As enterprises change the way they conduct business, we should also change our traditional approaches to data governance.
In his latest discussion, Profisee Head of Data Strategy Malcolm Hawker talks with Moxy Analytics CEO Laura Madsen to dive deeply into the topic of data governance and discuss Laura’s love/hate relationship with a field that can often defies logic in today’s modern data estates. Laura challenges many of the more traditional approaches to governance that are clearly not working for many companies — most of which have not changed fundamentally in decades. Laura makes a compelling case to “blow it all up” and start completely from scratch with approaches to data governance that are more scalable and adaptable to modern business needs.
Throughout the discussion, Laura takes aim at other data management gold standards, including what she sees as the absurdity of aspiring to a single definition for anything today. Laura advances the idea that data quality is not absolute and that striving for data quality standards that aren’t defined or measured is a fool’s errand. The discussion of data quality not existing without data governance — and vice versa — is an insightful exploration into the critical need to measure and define data quality metrics and standards. Laura highlights the paradox that having one without the other makes it impossible to know if you succeed at either quality or governance.
Laura highlights other data-related technologies as critical components to enable scale while also acknowledging they cannot “magically solve all of our problems.” The discussion concludes with a focus on the radical democratization of data, a concept that Laura believes is critical to breaking through old, unproductive patterns of data management. In this transition toward data democratization, Chief Data Officers (CDOs) will know they are on the right path when an environment exists for users to question the data, where those questions form the foundation for ongoing data improvements.
This episode of CDO Matters should appeal to any CDO who feels their data governance program is ill-suited to support their ever-evolving business needs. It should inspire CDOs to revisit their assumptions about data governance — and potentially motivate many to consider some radical changes to governance “business as usual.” Forget what you think you know about single sources of truth, data quality metrics or top-down approaches to governance — Laura Madsen challenges all of these concepts (and more) in this provocative episode of CDO Matters.
Key Moments 3:18 The Current State of Data Governance
5:23 “I Hate Data Governance”
7:16 Data Governance is Broken
8:45 Illogical Approaches to Data Governance
10:13 Data Stewardship for A Different Era
11:38 Do We Need Centralized “Command & Control”
14:28 Don’t Rely on a Single Definition of Your Data
17:59 Data Quality is Not Absolute
20:23 It’s Difficult to Prove Governance is Working without Data Quality and a Metric
22:33 Leveraging Data Governance Technologies
25:50 The Radical Democratization of Data
28:11 Data Governance Starts with People
29:38 Data Governance is Change Management
30:28 The Gender Gap in Technology
Key Takeaways The Way We Think about Data Governance Doesn’t Make Sense (4:40)
“When I see something that is wrong or lacking logic — and I do think that a lot of the ways we think about data governance now lack logic in a modern data environment — I just tend to want to blow those things up. There’s a fair part of me that still struggles with data governance as a result…we’re still doing a lot of the [traditional approaches].” — Laura Madsen
Illogical Approaches to Data Governance (7:54)
“I never intended to write a book about data governance. That was never on my radar at all…I was building a modern data platform and I didn’t really care about the landscape. Fast forward, I leave that job…the thing that kept coming back to me was that data governance was the Achilles heel of most programs and our ability to deliver results.” — Laura Madsen
Data Governance for a Different Era (10:23)
“In a space where in the late 90s, most of our data warehouses were maybe a handful of tables…nothing in terms of the construct of data governance changed from the late ‘90s to when I Googled that definition in 2019. Two decades…why are we still doing the same things with data governance in the data space?” — Laura Madsen
The Importance of Context in Data Governance (15:40)
“In what reality do we want everyone to be operating on one definition of something?...I want you to look critically at what you are executing and what is not working…Let [data leaders] have different definitions…When it matters is when you want to have a better sense of management around [definitions].” — Laura Madsen
Focus More on Process, People and Culture than Technology (22:53)
“We [initially] had no tools in this space at all…Data catalogs are changing the game. They help you focus on usage to define your use case…more eyeballs on the data means better data…tools can help us with that, but they cannot solve all of our problems. These are all problems that can be solved with some thinking about process and people and the culture of an organization and way less focus on the technology.” — Laura Madsen
Closing the Gender Gap in Technology (32:53)
“If we’re not willing to face these things and have discussions about them, then we are never going to improve them…We have made improvements and I sometimes think we need to acknowledge at least that…but, we still have a long way to go…it’s intentionality. It’s making yourself uncomfortable, realizing you have some culpability there, and moving forward.” — Laura Madsen
About Laura MadsenLaura Madsen is the CEO of Moxy Analytics and the author of three books on the topics of BI/Analytics, Data Strategy and Data Governance. With over 20 years in the field, she is a leader in the data and analytics industry and has supported the definition and implementation of data strategies and analytics/governance programs at multiple organizations across the country. She's a selfless champion for diversity, inclusion and gender equity matters through organizations like Sistech. Laura is also a Halestorm fan, myth-buster, BS caller and has perfected the art of cynicism.
EPISODE LINKS & RESOURCES:• Follow Laura Madsen on LinkedIn
• Purchase Laura’s book, Disrupting Data Governance: A Call to Action
• Learn more about Sistech, the Sisterhood of Technology Professionals
• Visit Moxy Analytics’ website
When it comes to leading a successful business, it is crucial to remain data-driven. But being overly technical in your approach can often take away from the social needs of your enterprise.
Malcolm and Dr. Juan Sequeda focus primarily on four key topics: data as a product, the data mesh phenomenon, why data leaders are incorrectly focused on technology and how taking a more ‘social’ approach — as advocated by the data mesh — will deliver superior results.
Dr. Sequeda breaks down data-related technologies into three core principles that he argues have changed little over the last several decades. CDOs with more of a business or non-technical background will appreciate how Dr. Sequeda is able to distill the complexities of the modern data estate into a simplified model — and warns how various data management vendors continue to complicate by focusing too much on software tools and features.
While exploring ways for data leaders to extricate themselves from technology-first approaches, the two explore the growing trend towards data as a product and how CDOs can benefit from it. Dr. Sequeda shares his ‘ABC’ framework for approaching data as a product that CDOs from all backgrounds can quickly use within their data organizations.
Dr. Sequeda both challenges and acknowledges the benefits of data centralization during a discussion focused on how master data management (MDM) is still needed by all organizations despite the decentralized approach advocated by the data mesh. Ultimately, it should be no surprise that a noted scholar on knowledge graphs believes that context and semantics should drive more modern approaches to governance and MDM — where the context or use case of data ultimately determines what rules/policies should be defined rather than the data itself.
This episode of CDO Matters will help less technical CDOs understand the underlying data semantics and why the data mesh — most especially the ‘data as a product’ phenomenon — is worthy of consideration. Prioritizing efforts to integrate product management disciplines in data management — at both centralized and decentralized levels — will ultimately help data leaders to drive superior results by being more driven socially.
Key Moments* [4:24] Bridging Tech and Business * [6:06] Defining Data Mesh for Your Organization * [8:20] A Social-first Approach to the Data Mesh * [10:52] What Comes After Data Decentralization? * [15:10] The 3 Principles of the Data Stack * [16:01] Modern Data Developments and How Data Software Categories Drive the Conversation * [17:05] Social vs. Cultural Business Approaches * [20:15] Metadata Serving as the Glue Behind Data * [23:12] Operational Focus of the Data Mesh * [25:20] The Relevance of Master Data Management (MDM) Today * [28:30] Powering a Data Fabric with a Semantic Layer * [33:20] Data Centralization through Governance
Key TakeawaysBridging Technology and Business for CDOs [5:05 — 6:03]
“I would say you need to have people on your team who can be those bridges…who will be able to fill that gap [between technology and business]. As a leader, you want to understand the overview of things, but you also want to feel empowered by having the best people around you.” — Dr. Juan Sequeda
Is Data Mesh a Software Category? [7:16 — 8:14]
“Data mesh is a social-technical paradigm shift, it is not something you buy… if somebody is selling you a data mesh, please run far away as fast as you can from that vendor because they are selling you B.S.” — Dr. Juan Sequeda
The 3 Principles of the Data Stack [15:06— 16:49]
“We talk about the modern data stack…look at the principles…here is this box and it has inputs and outputs. It is the three main boxes. One is the box that moves data. Data comes in, data comes out. Then you have another box where data comes in, questions come in and answers come out. That is your storage and compute…then you have another box where different questions come out. That is your analytics.” — Dr. Juan Sequeda
The Problem with Being Overly Tech-Focused [17:05 — 17:42]
“The issue here is that we have been defining success from a technical perspective, which is ‘my data is now in one place,’ but that was not the goal…define success from the social perspective about the needs of the business.” — Dr. Juan Sequeda
About Dr. Juan SequedaDr. Juan Sequeda is the Principal Scientist at Data.World and the co-host of the Catalogs & Cocktails podcast. Juan holds a Ph.D. in Computer Science from the University of Texas at Austin and is a noted scholar and researcher in the fields of semantic technologies, including knowledge graphs. He is a frequent public speaker at data and analytics conferences across the globe and is passionate about helping data leaders implement more modern and innovative approaches to both data strategy and data management.
EPISODE LINKS & RESOURCES:* Connect with Juan on LinkedIn * Visit Data.World * Check out the Catalog & Cocktails podcast
Successful companies don’t just withstand disruption, they find ways to innovate throughout technological change.
In this episode of CDO Matters, Malcolm interviews Dr. Cheryl Flink, an author and noted researcher in the field of human-centered design and social psychology.
Dr. Flink shares insights from her upcoming book, “Doing Well and Doing Good — Human Center Digital Transformation Leadership,” set to release in March 2023. She makes the case that digital transformation represents a fundamentally different way of operating, one that represents an optimal intersection of business, social and employee success.
She proposes that a successful digital transformation is one that prepares organizations to withstand — and even prosper from — the constant disruption of technology, where the delivery of human value is as important to financial value.
In addition to making a strong case for a human-centered focus within digital transformations, Dr. Flink also shares some of the keys to digital transformation success — most notably the need for a strong mandate from senior leadership — something many companies still struggle with. Having broad awareness and consensus around the ‘why’ of a digital transformation is the foundational level of a ‘scaffold’ approach to a framework for digital transformation that Malcolm discusses with Dr. Flink — outlined in more detail in her book.
Dr. Flink also makes the case for creating the corporate culture needed to allow for employees to feel safe to highlight imbalances between any of the various tensions that naturally exist within organizations — for example — between speed/agility and governance. The more balanced these forces are — and the more employee or stakeholder needs play an equal role to financial needs — the more human centered the approach will be. This is exactly what Dr. Flink sees as the optimal approach for long-term social and business success.
This episode of CDO Matters is perfect for those CDOs who have been tasked to execute a digital transformation strategy and who are looking for alternatives to more traditional program management approaches to these large-scale business initiatives. This episode explores how using more human-centered design approaches could optimize not only shareholder value, but also employee and social value. Dr. Flink makes a compelling case that ‘doing good and doing well’ is not only preferred, but increasingly required during a time of constant disruption and social scrutiny of business practices.
Key Moments* [3:55] What is Human-centered (HC) Leadership? * [7:10] Who Should Reap the Profits of AI/Digital Technology? * [10:45] Human-centered Leadership’s Role in Environmental, Social Governance (ESG) * [13:20] Leadership Benefits of HC Leadership * [14:15] HC Leadership in Digital Transformation * [16:00] A New Way to Work * [19:40] Applying HC Leadership to Data Strategy * [24:25] Differences in Approaching a Digital Transformation * [28:50] The Decision-Making Process * [31:35] HC Leadership Investments
Key TakeawaysThe Significance of Human -Centered Leadership [5:40 — 6:50]
“Are we really thinking about how we create human value? Not just financial value...I think that in this human centered leadership world, it is about the ability to think through that calculus...We think about that human value as including two major components: one is the value we are creating for individuals and the corporations we work with and the other is for society at large.” — Dr. Cheryl Flink
Digital Transformation Defined [14:45 — 15:35]
“The ongoing process of strategic renewal that uses advances in digital technologies to build capabilities that refresh or replace an organization's business model, collaborative approach or culture. In other words, you are preparing the organization for the constant disruption of technology.” — Dr. Cheryl Flink
Transitioning to a Human Centered Data Organization [21:25 — 22:04]
“You cannot move forward with digital transformation unless there is a transformational mandate. Why are we doing this? If that ‘why’ is not clear…the organization is going to flounder. They have to know why in order to create directional alignment and commitment. Alignment is we know how we are going to get there and commitment is we are all going to band together to make this happen.” — Dr. Cheryl Flink
The Tension Between Business Innovation and Governance [26:00 — 27:25]
“When you think about these teams that are innovating, they are rewarded for taking risks...fast release of products. The seamless integration team is rewarded for protecting data...for making sure that what is produced integrates into the current platforms. I have to innovate and I have to have business continuity. So, one of the things that a leader, to create human value, has to do is really create psychological safety...and balance that tension. ” — Dr. Cheryl Flink
About Dr. Cheryl FlinkDr. Cheryl Flink is the former Global Vice President for the Center for Creative Leadership. She helped organizations around the globe find new market opportunities, improve revenue and cost drivers and create exceptional customer experiences by linking data, technology and analytics to strategy, product development and business execution. Dr. Flink is currently applying her lengthy career in data, leadership, and research to the area of human centered business transformation.
EPISODE LINKS & RESOURCES:* Follow Dr. Flink on LinkedIn * The Center for Creative Leadership’s website * More on Human Centered Design
Episode Overview In this episode of CDO Matters, Malcolm interviews John Moran, the Director of Enterprise Data Governance with Thermo Fisher Scientific — a $40BB publicly traded manufacturing and services company providing innovative products and solutions to research scientists around the globe. In his role, John is responsible for establishing and maintaining enterprise-wide data policies, standards and processes across domains, supporting customers and products in some of the most complex and regulated industries on the globe.
Throughout their conversation, Malcolm digs into how John’s team has helped create a culture of data governance at Thermo Fisher, turning a potential obstacle into a value-add for their business. Through the efforts of the data governance team, Thermo Fisher has developed a culture of data governance as a business enabler and not just a regulatory requirement. Even with a complex and fragmented environment of over 100 ERPs and other core business systems, John’s team delivers data governance value through a focus on three key pillars:
- Listening to customer needs and speaking the language of the business
- Focusing only on data that matters and prioritizing governance efforts only on that data that will move the needle for the business.
- Engaging in business process analysis, where those responsible and accountable for data governance policies have an intimate understanding of how end consumers (not just internal customers/stakeholders) use data, and how policy changes have downstream impacts.
In other words, Thermo Fisher takes a “data as a product” approach to data governance to differentiate themselves from the competing product management companies. This is most certainly a valuable lesson for CDOs who are considering more product-centric approaches to managing their data — regardless of if they plan on monetizing data or not.
Another key takeaway for CDOs is the benefits Thermo Fisher has realized through effective prioritization of data governance efforts — which are a function of better listening, a deep understanding of how data drives business value and a focus on process analysis. In our near 30-minute conversation, John never uses the word “domain” to describe how they prioritize their understanding of business value — a key lesson for any CDO wanting to more closely align with their business instead of their data.
Key Moments [3:41] Keys to Data Governance Success
[5:40] Highlighting Customer Needs with Product Management
[10:00] Data Governance Prioritization
[12:18] Unlocking the Value of Data
[13:52] Taking a Business-centric Approach to Data Governance
[15:16] The Relation Between ERP Consolidation and Governance
[18:05] The Role of Thermo Fisher’s Data Governance Team
[19:10] Turning Back the Clock: Data Governance Takeaways
[21:10] Creating a Compelling Governance Message to Drive Value
[22:05] Business Literacy and Understanding Potential Value
[22:59] Shifts in Leadership
Key Takeaways Data Governance Obstacles [4:09 — 5:31]
“What I would say in terms of driving success...is that data governance can mean many things to folks. Sometimes they don’t conjure up the best images of things. You sort of have to get past that barrier...try to figure out where they are and meet them where they’re at. Get past the terminology and try to develop some common understanding of what data they are working with and what their challenges are.” — John Moran
Assembling a Strong Governance Team [13:52 — 14:44]
“What I really wanted were people who were ready, willing and able to learn… who have demonstrated the ability to grasp complex topics… because with data, especially product data, we are collecting and managing hundreds of data attributes and there is logic all over the place… People who were the most successful really understood the supply chain and what happened downstream and were able to explain that to other people…. We encourage our team to understand all of the downstream impacts [of data].” — John Moran
Benefitting from Governed Data [17:07 — 20:18]
“With so much data, if you treat everything with equal importance, you sort of lose your way...[You need to consider] what are the decisions we plan on making with governed data that we can't make today...and then connecting that and quantifying that…Then you are not talking about data governance for data governance’s sake, you are talking about enabling whatever that financial benefit is.” — John Moran
Communicating with Executive Leadership [21:25 — 22:04]
“[Process analysts] need to be able to speak the language that our executives speak: making money, saving money, reducing risk. If you can't connect [data efforts] to one of those three things, it's going to be hard to change behaviors.” — John Moran
About John Moran John Moran is the Director of Enterprise Data Governance for Thermo Fisher Scientific. He previously worked with Intuit before transitioning to his current position of 16 years. John is Six Sigma Black Belt certified in techniques and tools for process improvement.
EPISODE LINKS & RESOURCES: * Follow John on LinkedIn * Listen to John Moran’s appearance on The Data Standard podcast * Learn more about Thermo Fisher at their official website
Episode Overview In this episode of CDO Matters, Malcolm sits down with West Monroe’s Data & Analytics Strategy Innovation Fellow, former Gartner analyst and best-selling author Doug Laney to discuss the business value that can come from data. Doug’s book, Infonomics: How to Monetize, Manage, and Measure Information for Competitive Advantage, was selected by CIO Magazine as the “Must-Read Book of the Year,” a “Top 5 Books for Business Leaders and Tech Innovators,” and by the Wall Street Journal as one of its “5 Summer Reads for CIOs.” His latest book, Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets has received accolades from business, data, analytics and IT executives and practitioners around the world.
During their discussion, they touch on key data value topics including how to measure data as an asset within your organization, the overall state of data management, evaluating data context and reporting on the actual value that critical data brings. They go on to talk about alternative forms of data value (e.g., tokenized data, cryptocurrencies) and how the principles of his latest book apply to real-world business use cases.
The conversation closes with the two weighing in on what they believe the future will be like for enterprise data strategies before concluding on the importance of sharing data governance within your business.
*Stick around to the end of the podcast as Doug makes you a valuable offer you don’t want to miss*
Key Moments [4:53] The Importance of Info-nomics
[9:00] Measuring Data as an Asset
[12:23] The State of Data Management
[15:03] Evaluating Data Context
[19:33] Reporting on the Value of Data
[23:53] Alternative Data Values – Tokenizing Data & Crypto
[25:43] Applying ‘Data Juice’ to Real-World Use Cases
[31:03] The Future of Enterprise Data Strategy
[35:23] Sharing Data Governance
Key Takeaways The 3 Ms of Info-nomics: Measure, Manage and Monetize [6:51 – 8:55]
“With [CDOs], the role is still kind of being defined…it’s really about how to manage and leverage data as an actual asset. That’s really what’s at the core of what [CDOs] need to be doing to drive and prove value from data.” – Doug Laney
How to Measure the Monetary Impact of Your Data [8:57 – 9:55]
“The state of data management...I would give it about a five or maybe a solid six [out of 10] ...Getting back to the notion of measuring, what I would hear all the time from all the CDOs and CIOs…is that the impacts here from a data perspective are indirect.” – Malcolm Hawker
Improving the Data Process for Better Performance [10:24 – 11:20]
“We developed an entire metrics framework…that can be used to empirically track how improvements in various quality metrics and data governance indicators drive improvements in business process performance leading to revenue improvements, profit improvements, market share, risk reduction, etc.” – Doug Laney
Why Value Your Data? [17:06 – 19:10]
“Depending on why you want to value the data, whether you are trying to get investments or whether you are trying to justify the benefits of an analytic use case …there are a variety of reasons that you would want to value your data...the standards methods of evaluating any asset are the cost approach, the market approach and the income approach.” – Doug Laney
Reporting on Data Value [20:00 – 22:07]
“If data was a balance sheet asset, I think it would help some organizations and hurt others...there are certain things that you want to keep proprietary and out of the prying eyes of investors and competitors...If you could report on the value of your data, it might augment the evaluation of your company…Data is not a balance sheet asset according to accounting standards.” – Doug Laney
About Doug Laney Doug Laney is a best-selling author and recognized authority on data and analytics strategy. He advises senior IT, business and data leaders on data monetization and valuation, data management and governance, external data strategies, analytics best practices and establishing data and analytics organizations.
EPISODE LINKS & RESOURCES: Follow Doug on LinkedIn
Doug’s Published Works:
- Infonomics: How to Monetize, Manage, and Measure Information for Competitive Advantage
- Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets
Episode OverviewIn this episode of CDO Matters, Malcolm interviews Sanjeev Mohan. Sanjeev is a fellow former Gartner data and analytics analyst and is the founder of SanjMo, a professional services organization focused on helping organizations discover opportunities for market advancement and company growth through outsider insights into their data analytics, internal processes, customer feedback and competitors.
This episode of CDO Matters was recorded live at the 2022 CDO IQ Conference on the campus of MIT in Cambridge, Massachusetts. Malcolm and Sanjeev discuss their key takeaways and learnings from the sixteenth iteration of this annual conference focused exclusively on the needs of CDOs from across the globe.
This podcast helps CDOs better understand the benefits of attending this conference in the future, what sets this conference apart from others and what some of the top trends are within the data and analytics space discussed at the conference. CDOs will also appreciate some unique insights on the evolution of the CDO role, as reflected through the conversations with the many CDOs attending this unique conference. For CDOs looking to attend more industry events and seeking to build their professional networks, CDOs will better understand if the CDO IQ conference is the right fit for their business needs.
Key Moments * 2:45 Key trends as reflected through conversations and presentations at the CDO IQ conference * 7:52 Caliber of networking experienced at the CDO IQ conference. * 13:20 Vendor focus at CDO IQ * 19:46 Malcolm and Sanjeev discuss life after Gartner * 29:26 Common themes heard during conversations with CDOs at CD OIQ * 31:35 The future of data management
Key Takeaways The Expanding Role of the CDO (2:54–4:02)
“CDOs are getting much more tightly integrated with businesses...it is all about monetizing, democratizing and getting value out of your data.” - Sanjeev Mohan
How Product Management is Becoming Integrated with Data Management (4:42–5:29)
“On a high level, I think it is a really good trend. This trend towards product management in the data management space.” - Malcolm Hawker
The Value of the Entire Data Lifecycle (6:06-6:49)
“Data as a product has become so important...we think of its entire lifecycle.” - Sanjeev Mohan
The Unique Opportunity of the CDO IQ Conference (7:52-8:51)
“To me, [networking] is the highlight of this conference...these are the senior-level decision-makers with decades of experience....and just learning from them.” – Sanjeev Mohan
The Importance of Data Storytelling (17:46-18:44)
“It’s easy for technology people like us to say that we aren’t salespeople...but at the heart, it is being able to tell the data story.” – Malcolm Hawker
About Sanjeev Mohan Sanjeev is a former Gartner data and analytics analyst and the co-host of the It Depends podcast. He is also the principal and founder of SanjiMo, a professional services firm helping companies become more data-driven. As former Gartner analysts, Sanjeev and Malcolm spent time working together in the data space.
Episode Links and Resources:* Follow Sanjeev Mohan on LinkedIn * IT Depends
Episode OverviewIn this episode of CDO Matters, Malcolm interviews the President and COO of BlueConic, Cory Munchbach. Cory is a fellow recovering analyst and runs one of the top Customer Data Platform, or CDP, solutions available in the market today. In her role, Cory is at the forefront of some of the biggest customer experience and digital transformation initiatives of many of the best-known brands on the planet.
During their discussion, the two focus on the role of women in technology and how we can improve on the many gender imbalances that continue to persist both in their companies, and society at large.
They also discuss the role of CDPs in the digital transformation landscape, and how those solutions differ from other customer-data management solutions – such as MDM or analytics platforms. If you are one of the 25% of CDOs tasked with executing your organization’s digital transformation initiative, this episode of CDO Matters will help bring you to a higher-level understanding of how CDPs ‘fit’ into a broader MarTech and IT technology stack, and the value they bring to the organization.
The conversation closes with a dialog around the possibility of a coming recession, and what CDOs and other senior leaders can do to best prepare for some form of economic slowdown. Cory shares her experience in working with major consumer-facing brands over the last recession, and how many ‘doubled down’ digital transformation investments as a means to improve customer relationships and drive competitive advantage.
Key Moments * 01:56-4:43 The current market of Customer Data Platforms (CDPs) * 04:56-6:30 Activating customer data throughout the organization with CDPs * 6:35-7:35 How do Chief Data Officers (CDOs) benefit from CDPs? * 8:00-11:31 How CDPs can co-exist with master data management (MDM) * 11:42-14:22 Thoughts on the underrepresentation of women in leadership positions in tech * 15:04-18:05 Pay transparency as a catalyst for equality in the workplace * 18:15-18:58 Being the only woman on the leadership team * 19:06-21:58 The impact of tech companies on expanding access to benefits * 22:10-24:33 How CDOs can respond to economic uncertainty * 24:35-26:22 Building a data strategy around a clear business objective * 26:24-31:43 How GDPR, CDPA and other regulations will continue past 2022
Key Takeaways The Coexistence of CDPs and MDM (9:15-9:37)
“I would have conversations…with IT leaders...about this false perception that it was either CDP or MDM. My answer always was both.” - Malcolm Hawker
The Underrepresentation of Women in Technology (12:06-14:04)
“...this is much less of a tech problem and more of a social problem...we’ve always had an underrepresentation of women in technology, so there haven’t been enough people to go to battle for the kind of things that will make more women come.” - Cory Munchbach
Pay Transparency in the Workplace (15:38-17:08)
“If you have a certain role...then everyone in that role should be within that pay band...over time, your value for the organization grows and we don’t make a lot of adjustments for that internal expertise...” - Cory Munchbach
Responding to Economic Uncertainty (23:19-25:24)
“I am a big believer that you should plan for the worst and hope for the best...this should be transformational because it changes how you work...the thing that you need to have is the relationship with your customer.” - Cory Munchbach
About Cory Munchbach Cory is the current President and COO of BlueConic. She previously worked as an analyst for Forrester supporting marketing technology and the former author of the Forrester ‘Wave.’ While being an early-stage startup investor and advisor, Cory also serves as a member of Chief – a private network designed for the most powerful women in executive leadership.
EPISODE LINKS & RESOURCES: * Visit BlueConic’s official company website * Follow Cory Munchbach on LinkedIn
Episode OverviewIn this episode of CDO Matters, Malcolm is a guest on the Data Engineering Podcast with Tobias Lacey. This episode is a great fit for any non-technical data leader who is looking to gain a deeper understanding of some of the technical dependencies and concepts required for successful master data management (MDM) and data governance — but without getting too deep into jargon or software engineering concepts.
If you’re a business-centric CDO with limited technical experience or background, this podcast will help you to build your data literacy and allow you to have deeper and more compelling conversations with your technical staff — and it will help you make more informed technology-centric decisions.
Malcolm and Tobias cover some of the technical concepts involved in MDM and governance programs — in both relatable and understandable terms — including:
- MDM systems architecture and typical implementation patterns
- The connection between MDM, data engineering and systems architecture
- Data modeling for MDM and data governance
- The processes used in MDM platforms to support data quality requirements
- Entity resolution, i.e., matching or deduplication
- MDM team dynamics and roles, the role of data stewardship.
After listening to this podcast, any data leaders who may be new to the concepts of MDM or data governance will why their organizations need these foundational elements and better understand how they can be used to drive business benefit.
Key Moments* 3:14-6:50: Identifying ‘who is a customer’ to model and govern data * 7:11-9:27: What is MDM and how does it add value? * 10:27-14:57: Who needs MDM and how does new technology solve for data quality? * 15:11-17:53: Limitations and considerations when searching for a “single source of truth” * 18:15-21:45: Who is responsible for MDM within an organization and who comprises it? * 22:16-26:59: What are the differences between analytical and operational MDM? * 29:15-31:50: Top 4 reasons that so many MDM implementations fail * 32:45-36:40: Using a business perspective to identify the right outcomes * 37:40-42:25: How MDM is evolving to use graph functionality in addition to relational databases * 42:32-43:15: Why Customer Data Platforms (CDPs) fall short for enterprise-level management * 43:36-49:51: Insights on novel MDM use cases: data sharing, graph databases, data fabrics * 50:08-53:53: 3 ‘Watch-outs’ learned from years in the data management space * 54:36-57:26: How small companies can implement MDM principles * 57:38-1:00:14 The gap between data software and real business outcomes
Key TakeawaysWhen is MDM relevant for an organization? (10:22-11:34)
“The bigger and more complex you are and the more decentralized you are...where organizations are struggling to have a single view of the customer...the larger the company, the more they tend to have a need for MDM.” - Malcolm Hawker
Cloud-native data warehouses vs. MDM software (15:11-16:33)
“There are many cloud-based data warehouse technologies that are saying we can enable a single version of the truth, and they absolutely can...but does it have all the flexibility and reconfigurability to allow for all the things that MDM software can do? Typically, they don’t.” - Malcolm Hawker
What are the differences between analytics and operational MDM?? (23:51-26:22)
“An analytical style of MDM is where the flow [of data] is one-way...[operational MDM] can actually turn around and syndicate that data back down into consuming systems.” - Malcolm Hawker
4 MDM pitfalls to avoid during your implementation (29:15-31:01)
“If you’ve got a need for MDM and if you have been given a mandate by your management to come up with a single version of the truth...avoid the key pitfalls that often send so many MDM programs sideways.” - Malcolm Hawker
Companies of all sizes can benefit from MDM principles (57:05-57:26)
“I would argue that most companies need MDM as a discipline...But chances are, you still have some use cases that need that consistent approach to the data management side...” - Malcolm Hawker
About the GuestTobias Macey is a dedicated engineer with experience spanning many years and even more domains. He currently manages and leads the Technical Operations team at MIT Open Learning where he designs and builds cloud infrastructure to power online access to education for the global MIT community. He also owns and operates Boundless Notions, LLC where he offers design, review, and implementation advice on data infrastructure and cloud automation.
In addition to the Data Engineering Podcast, he hosts Podcast.__init__ where he explores the universe of ways that the Python language is being used. By applying his experience in building and scaling data infrastructure and processing workflows, he helps the audience explore and understand the challenges inherent to data management.
EPISODE LINKS & RESOURCES:* Connect with Tobias Macey on LinkedIn * Subscribe to The Data Engineering Podcast
In the inaugural episode of the CDO Matters Podcast, Profisee Head of Data Strategy and former Malcolm Hawker speaks to his former colleague, “The Data Whisperer” Scott Taylor, on the art and science of data storytelling — and how to frame the critical importance of trusted data in a way that resonates with business leaders.
In his years of consulting, speaking and writing on all things master data and data management, Scott has developed a unique storytelling approach to make sense of complex ideas in ways that prompt business leaders to action and get funding for enterprise data projects.
Malcolm and Scott discuss why business leaders don’t care about the technical or dogmatic approach to data management and CDOs can hone their storytelling abilities to deliver a pitch with passion, clarity and effectiveness. They push past the buzzwords, trends and stodgy approaches to data management and stress the importance of starting any data initiative pitch with “why.”
And despite the reality that most business leaders will never care about data for its own sake, they close the conversation with a sense of optimism and hope about the future of high-quality, trusted data in the marketplace.
Key Moments* 01:30 CDO Matters: A new approach to data storytelling * 05:20 Creating a compelling narrative for business leaders * 05:52 What to avoid starting with — and leading with ‘why’ * 08:30 The 3 Vs of Data Storytelling * 10:15 Honing data storytelling abilities * 13:50 Leading your pitch with Passion * 16:03 Should you try changing the data culture? * 17:52 Forget the dogmatic approach to data management * 21:14 Data is fuel, not the exhaust * 12:16 Showing vulnerability as a data leader * 22:52 The importance of a consistent data philosophy * 23:36 Why businesses don’t care about data quality * 24:42 Optimism about the future of data management
Key TakeawaysCreating a Compelling Narrative around Data Initiatives (4:43-5:32)
“There’s this idea you have to create a compelling narrative that the business would understand so they can really support and literally fund the work that was so important in the data management space…” - Scott Taylor
Honing Your Storytelling Abilities (10:21-11:05)
“I think everybody is a born storyteller...they’ve got to be human and to be successful in business...you’ve got to be able to convince someone of the benefits of the offer or articulate some kind of need.” - Scott Taylor
Vulnerability as a Data Leader (12:16-12:54)
“These are lessons for CDOs as well, and one of them is vulnerability...if you are in front of a large group, particularly technology folks, you say, ‘Here are the things that I can’t do’...” - Malcolm Hawker
The Unique Impact of Data Professionals (17:00-17:49)
“There’s not another group [data professionals] in an organization that can bring value to every other part of the company…financing, sales, operations…” – Scott Taylor
Forget the Dogmatic Approach to Data Management (17:52-18:40)
“If I’m being told I need to change the [data] culture…and what don’t you understand about how important data is, if I am managing a supply chain or selling something, that doesn’t really resonate with me…” – Malcolm Hawker
About the GuestScott Taylor, also known as The Data Whisperer, has helped countless companies by enlightening business executives to the strategic value of master data and proper data management. He focuses on business alignment and the “strategic WHY” rather than system implementation and the “technical HOW.” At MetaMeta Consulting he works with Enterprise Data Leadership teams and Innovative Tech Brands to tell their data story.
EPISODE LINKS & RESOURCES:* Follow Scott on LinkedIn * Scott’s 2020 book, “Telling Your Data Story” * Scott’s ‘Data Whisperer’ explainer videos