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Data teams spend enormous energy building pipelines, platforms, and governance frameworks but often skip the most fundamental step: truly understanding what people are actually asking for. In this episode, Juan and Tim sit down with data librarians Jenna Jordan and Amalia Child to explore why library science may be the missing lens for data work. At the heart of the conversation is the reference interview, a structured technique librarians use to uncover a user's "true information need," which almost never matches the first question they ask. From establishing trust and listening without judgment, to asking open-ended questions and verifying whether the need was actually met, the reference interview offers a rigorous, repeatable framework for anyone serving data users. If you've ever wondered why data projects deliver less value than expected, this episode will reframe the problem entirely and give you a practical toolkit to start closing the gap. See omnystudio.com/listener for privacy information.

Data teams obsess over pipelines and platforms but often skip the most fundamental step: truly understanding what people are actually asking for. We chat with data librarians Jenna Jordan and Amalia Child who share a framework for exactly that; it's called the reference interview, and it might be the most practical toolkit data teams have never used. See omnystudio.com/listener for privacy information.

There's a gap at the heart of most organisations and data hasn't filled it. Pete Williams, an experienced data leader, has spent years watching companies build sophisticated data capabilities, only to see insight stall before it reaches action. In this episode, we diagnose why: organisations still make decisions along traditional vertical lines, while data sits in a horizontal layer that was never given real authority. AI doesn't solve this misalignment, it exposes it! Pete makes a compelling case for why fixing this structural void is the defining challenge for data leadership today. See omnystudio.com/listener for privacy information.

This is the takeaway episode with Pete Williams, an experienced data leader, who argues that organisations still make decisions along traditional vertical lines, while data sits in a horizontal layer that was never given real authority. Pete makes a compelling case for why fixing this structural void is the defining challenge for data leadership today. See omnystudio.com/listener for privacy information.

Juan and Tim have a rant session with a special guest in person, Jesús Barrasa, well known in the knowledge graph space. We covered AI trends, the balance between operational vs. strategic work, knowledge graphs, context graphs. The most valuable part of our rant was our pragmatic discussion about ontologies stripping them down to what they actually are and why they matter. Starting to work with ontologies? Think about these two dimensions: WHAT (Formal, Explicit and Shared Meaning) and WHY (Interoperability, Automation). See omnystudio.com/listener for privacy information.

Most organisations know they're not getting value from their data and AI investments, but few are willing to name the real culprit: the boardroom. In this episode, Kyle Winterbottom joins Juan and Tim to argue that the mandates handed to CDAOs are fundamentally broken because the people hiring them don't understand what good looks like. Boards continue to build capability without starting with the end in mind, creating a culture where data leaders are rewarded for building things rather than delivering outcomes. The result? An entire industry that has learned to play the wrong game.  See omnystudio.com/listener for privacy information.

This is the takeaway episode with Kyle Winterbottom where he argues that the mandates handed to CDAOs from the board are fundamentally broken because the people hiring them don't understand what good looks like. The result? An entire industry that has learned to play the wrong game.  See omnystudio.com/listener for privacy information.

Stop treating AI governance like a compliance checkbox handed down from the boardroom. Kierra Dotson joins Juan and Tim to argue that the chasm between ambitious AI strategy and messy technical reality exists precisely because we've made governance someone else's problem. The fix? Empower engineers, data scientists, and product owners to own their role in shaping ethical, sustainable AI — not as a burden, but as the thing that makes the work actually matter. See omnystudio.com/listener for privacy information.

This is the takeaway episode with Kierra Dotson where she argues that the chasm between ambitious AI strategy and messy technical reality exists precisely because we've made governance someone else's problem.  See omnystudio.com/listener for privacy information.

What does dentistry have to do with data analytics? More than you'd think. Thais Cooke went from cleaning teeth to cleaning datasets and her unconventional path turned out to be a superpower. In this episode, Thais joins Juan and Tim to talk about why subject matter expertise is the ultimate force multiplier, how to build trust with stakeholders (hint: "I don't know" is a valid answer), and why the best data professionals aren't technical specialists — they're problem solvers.  See omnystudio.com/listener for privacy information.

This is the takeaway episode where Thais Cooke joins Juan and Tim to talk about why subject matter expertise is the ultimate force multiplier. Oh, and what does dentistry have to do with data analytics? More than you'd think! See omnystudio.com/listener for privacy information.

Want to get the honest no bs scoop of what happened at the Gartner Data & Analytics in Orlando, then this short and sweet episode is for you. This was an impromptu recording where Sanjeev Mohan and Ryan Dolley join Juan and Tim to share what they learned.  See omnystudio.com/listener for privacy information.

Juan and Tim rant about whats on their mind going into Gartner Data and Analytics conference: "Context" is going to be the word of the week, The Execution Gap, Decision intelligence might be the bridge and the thing nobody's talking about yet: context lock-in.  See omnystudio.com/listener for privacy information.

Most data and AI initiatives don't fail on technology — they fail on meaning. In this episode, Juan and Tim chat with Säde Haveri, who makes the case that metadata is the bridge between systems and people: the language and structures that help humans understand, trust, and use data in their daily work. Her focus isn't on building smarter pipelines, but on turning complexity into shared understanding so that data actually drives decisions and behavior change. Because if your data doesn't speak your language, it simply won't work for you. See omnystudio.com/listener for privacy information.

This is the takeaway episode with Säde Haveri where she makes the case that metadata is the bridge between systems and people. Most data and AI initiatives don't fail on technology — they fail due to the lack of meaning. If your data doesn't speak your language, it simply won't work for you. See omnystudio.com/listener for privacy information.