CDO Matters Podcast

Episode SummaryUnleashing the power of Data Products, and transforming CDOs into Product Visionaries.In this the 28th episode of the CDO Matters podcast, Malcolm explores the topic of Data Products and what CDO’s should know about them. Malcolm taps his expertise as a prior Chief Product Officer to explore the differences between data products as they exist within a Data Mesh architecture, versus the more general concept of data products outside a Mesh. Malcolm takes issue with the idea of a ‘bottoms up’ approach to defining data products, and instead advocates that CDOs take a more practical view of a data product as anything that a customer is willing to pay for. Malcolm urges CDOs who are curious about data products to ensure they first establish a business justification for their efforts – one which focuses more holistically on the benefits that can come from the integration of the discipline of product management into a data and analytics function. Malcolm shares his insights that data products should be treated as an output of a product management focus, and the many benefits that are realized when CDO’s embrace the discipline of product management.Lastly, Malcolm dives into the role of a data product manager, sharing details on the core responsibilities for these experts and how they would differ from the concept of a data ‘owner’. Along the way, Malcolm touches on the misguided idea of data literacy, and how taking more a product-centric approach to building and supporting data solutions could enable CDOs to completely transform their customer relationships.Episode Links & Resources:Follow Malcolm Hawker on LinkedIn

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 interventionAbout 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 LinkedInFollow Bethany Lyons on LinkedInVisit 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:- The ethics behind using data for social concepts- Quantifying social data- Early stages of AI and the creation of data computation - The history of machine learning- The internet boom of the 90s- AI vs. copyright laws...and so much more!Episode Links & Resources:Follow Malcolm Hawker on LinkedInFollow Chris Wiggins on LinkedInCheck 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 fabricMalcolm's journey in releasing 20+ episodes of the CDO Matters podcastDefining data by its business value...and more!EPISODE LINKS & RESOURCES:Follow Malcolm Hawker on LinkedInFollow Ben Bourgeois on LinkedInRegister 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 ThoughtsKey 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 HawkerWhat 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 interestsMemorable life experiencesProfessional insightsOutlooks on the data spaceSources of inspirationLeadership qualitiesCurrent trends and happenings in the world of data and analyticsAnd 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 ChallengesKey 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 HawkerMalcolm’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 HawkerEssential 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 HawkerAbout 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 LinkedInFollow Samir Sharma on LinkedInVisit datazuum’s websiteListen 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 appearancesAnd 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 AppearancesKey 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 HawkerSeparating 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 HawkerSelling 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 TaylorAbout 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 LinkedInFollow Scott Taylor on LinkedInVisit MetaMeta Consulting’s website

Kyle Winterbottom, CEO of Orbition, discusses the scarcity of CDO roles and the struggle to define the role. The podcast also explores LED sign troubles, the disparity in job applicants for technical and leadership roles, the shift from data science to data engineering, building a data analytics culture, integrating product management into data management, and the short tenure of CDOs.