The Data Playbook Podcast

• Ep 3. Building Sustainable Data Products that actually get used - The Data Playbook Podcast: Kris Peeters & Geert Verstraeten

  In this episode of The Data Playbook, we dive deep into a critical, often-overlooked question: What does it mean to build sustainable data products? And no, we’re not just talking ESG dashboards or carbon reporting.🎙️ Host Kris Peeters is joined by Geert Verstraeten, a seasoned data scientist, founder of Python Predictions, and now a Co-Lead at The Data Forest—a consultancy that puts purpose and sustainability at the core of every data project.Over a candid and rich conversation, Geert shares:How he transitioned from startup founder to corporate leader and back to startup life—with a sustainability mission.Why many data projects fail not because of tech, but because of missed alignment and poor adoption.What sustainable data products really are: tools that not only minimize environmental impact, but also stand the test of time—well-documented, actually used, and aligned with real business needs.Why selecting the right clients and projects is the first step toward impact, not just profit.How the Data Forest scores potential engagements using a unique framework: Head, Heart, and Hands.💡 Along the way, you’ll hear thought-provoking takes on:The role of documentation in sustainability.Why good data work isn’t about building everything real-time or at scale—especially when you’re not Google.The paradox of GenAI and compute-heavy models in a world striving for tech responsibility.Whether you're a data engineer, architect, scientist, or team lead, this episode challenges you to rethink what a "good" data project looks like.👀 If you’ve ever built something technically brilliant that no one used, this episode is for you.Hit play to hear:What drives Geert and his team at The Data ForestHow to make better decisions on project scoping and client fitWhy data professionals need to talk to stakeholders much earlier—and more often

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• Ep 2. What Not to Build with AI: Avoiding the New Technical Debt in Data-Driven Organizations - The Data Playbook podcast: Kris Peeters, Tim Schröder, Pascal Brokmeier

  What Not to Build with AI: Avoiding the New Technical Debt in Data-Driven OrganizationsIn this episode of The Data Playbook, we explore a crucial and often overlooked question in the age of generative AI: not what to build—but what not to build.Host Kris Peeters (CEO of Dataminded) is joined by seasoned data leaders Pascal Brokmeier (Head of Engineering at Every Cure) and Tim Schröder (AI & Data Transformation Lead in Biopharma), to talk about the dark side of unlimited AI capabilities: technical debt, fragmented systems, and innovation chaos.Topics we dive into:Why generative AI lowers the barrier to building—but increases long-term complexityThe risks of treating LLMs as “magical oracles” without governanceHow RAG systems became the default architecture—and why that’s dangerousThe zoo vs. factory dilemma: how to balance AI experimentation with structureMaster data vs. knowledge graphs vs. embeddings – when and why each breaks downWhat Klarna got right (and wrong) by replacing SaaS tools with AI-generated internal appsThe growing importance of AI literacy, data maps, and platform thinkingReal-world examples of AI agents autonomously debugging systems—and when that’s terrifyingWe ask tough questions like:Are enterprises just building themselves into a new kind of mess, faster than ever before?Is the AI hype driving us toward “build now, regret later”?Should you really let every department build their own AI stack?Whether you're a data engineer, data architect, AI product lead, or a data strategist, this episode is a must-listen. We’re cutting through the hype to figure out where the real value is—and where the future tech debt is quietly piling up.🧠 Key quote:"If you can't tell me why you're building it, maybe you shouldn't be building it at all."💡 Tune in to learn how to stay smart, intentional, and strategic when it comes to building with AI.#TheDataPlaybook #DataEngineering #AIinBusiness #TechnicalDebt #RAG #LLMs #DataStrategy #EnterpriseAI #DataGovernance #DataLeadership #KnowledgeGraphs #GenerativeAI #AIinHealthcare #AIProduct #Dataminded

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• Ep 1. Building Data Architecture from Scratch: Cloud, Data Mesh, and the Real-World Tradeoffs - The Data Playbook podcast by Kris Peeters & Thorsten Foltz

  What does it really take to build a modern data architecture from the ground up? In our very first episode of The Data Playbook, host Kris Peeters, founder and CEO of Dataminded, sits down with Thorsten Foltz, seasoned data architect and engineer, to unpack what works (and what doesn’t) when designing scalable, future-proof data platforms.With a focus on real-world tradeoffs, this episode explores:Cloud vs on-prem vs hybrid: how to choose the right infrastructureThe rise of Data Mesh and when it actually makes senseWhy fake news isn’t just a media problem—it’s a data problem inside companies tooVendor lock-in, cloud sovereignty, and the growing relevance of European alternativesThe balance between open source and managed services: cost, control, and complexityWhy team culture and communication often make or break your data strategyWhat engineers can really expect from LLMs in the data stack (spoiler: they're not replacing data modeling any time soon)Whether you're a data engineer, architect, analyst, or tech leader, this conversation goes far beyond buzzwords. You’ll hear practical lessons, hard-earned insights, and a few uncomfortable truths about how companies actually manage data today—and how they should rethink it for tomorrow.

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