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.

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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.

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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.

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