The Data Playbook Podcast

Dataminded
  • 5.0 (1)
  • Technology
  • Updated daily

🎙️ The Data Playbook is a podcast where we aim to build a playbook for data leaders. We do that through a series of interviews with other data leaders, data practitioners and data experts. In each episode, we break down real-world data challenges: from building modern architectures and embracing Data Mesh to navigating cloud sovereignty, we help you make smarter decisions one play at a time.

  1. 5 days ago

    Agentic AI in Production: What Data Leaders Need to Know Before Scaling AI

    Agentic AI is everywhere. Production-ready AI is not. In this episode, Kris Peeters talks with Dataminded Data Engineer Jesus Garcia about the gap between AI hype and enterprise reality. Drawing on lessons from building a large-scale Agentic AI platform, they discuss security, governance, user adoption, change management, AI skills, and the future role of engineers in an AI-first world. For data leaders, CIOs, CDOs and technology executives, this conversation provides practical insights into what it takes to deploy AI systems that people trust and actually use. 🌐 More at https://www.dataminded.com/ Topics covered: Agentic AI, Enterprise AI, RAG, AI Security, AI Governance, Change Management, Data Leadership, AI Adoption, Data Engineering. Chapters: 00:00 Agentic AI in Production: Introduction 01:34 Enterprise Knowledge Management with AI Agents 05:19 RAG, Vector Search and Agentic AI Explained 07:36 Deploying Agentic AI at Enterprise Scale 12:14 AI Governance, Security and Access Control 17:06 What Data Leaders Can Learn from AI Security Incidents 25:34 Will AI Replace Software Engineers? 40:20 Why Coding Is Easier for AI Than Business Decisions 43:36 Real Productivity Gains from AI Skills and Automation 49:35 The Limits of Large Language Models 56:44 Change Management: The Real Challenge of AI Adoption

    58 min

  2. 11 Jun

    Can We Outsource Thinking? AI, Education, and the Future of Knowledge Work

    Agentic AI is changing how we build software, manage data, conduct research, and learn new skills. But as AI takes over more cognitive tasks, a fundamental question emerges: what capabilities do humans still need to develop themselves? In this episode, Kris Peeters sits down with Frank Neven, Professor of Computer Science at Hasselt University and Vice Director of the Data Science Institute, to discuss the future of data engineering, AI-assisted learning, database systems, and human-AI collaboration. The conversation explores: Why understanding remains essential in an AI-driven worldHow universities are adapting to AI-powered educationWhat the latest database research tells us about the future of data platformsThe rise of agentic coding and AI-native software developmentHow AI is transforming scientific researchWhy structured knowledge and semantic data are becoming more valuableThis episode is particularly relevant for data leaders, CIOs, CDOs, architects, and engineering teams navigating the rapid evolution of AI. 🌐 More at https://www.dataminded.com/ #DataEngineering #AgenticAI #DataLeadership #ArtificialIntelligence Chapters: 00:00 From Theory to Data Engineering 03:20 AI and Healthcare Data Integration 06:00 The Data Science Institute in Practice 19:00 Why Computer Science Education Matters 25:40 AI in Education: Opportunity and Risk 35:00 You Can Outsource Reasoning, Not Understanding 38:45 Agentic AI and the Future of Databases 45:50 How AI Is Changing Research 51:45 Personal AI Systems and Knowledge Management 59:30 Staying Open-Minded in Technology

    1hr 2min

  3. 9 Apr

    The Data Challenge behind the Einstein Telescope - The Data Playbook Podcast with Kris Peeters & Tjonnie Li

    What does it take to listen to the universe? In this episode of The Data Playbook, Kris Peeters talks with Tjonnie Li, Professor at KU Leuven, about gravitational waves, black hole collisions, and the massive data challenge behind the Einstein Telescope. They explore how modern science is becoming deeply data-driven, why the next generation of research infrastructure will need to operate like a science factory, and how AI, automation, and large-scale compute could become essential for turning petabytes of raw data into scientific discovery. This episode covers: what gravitational waves are and why they matterhow black hole collisions are measuredwhy the Einstein Telescope could transform European sciencethe data, compute, and storage challenge behind next-gen physicswhat academia can learn from industry about automation and orchestrationhow AI agents could support future scientific discovery👉 Subscribe for more episodes: https://www.youtube.com/@Dataminded 👉 Watch on YouTube: https://youtu.be/aBbykwnsmpI 👉 Explore more content & insights: https://dataminded.com 👉 Follow Dataminded on LinkedIn: https://www.linkedin.com/company/dataminded #DataEngineering #AI #GravitationalWaves #EinsteinTelescope #BigData #ScientificComputing #ResearchInfrastructure #DataPlaybook Chapters: 00:00 Intro: Tjonnie Li joins The Data Playbook 02:08 What gravitational waves are - in plain English 05:19 Why science is becoming data-driven 11:28 How we measure black hole collisions today 15:50 The Einstein Telescope: ambition, timeline, and European bid 19:44 The data infrastructure challenge: from terabytes to petabytes 30:56 AI, automation, and the idea of a “science factory” 38:50 Why this matters for Europe, innovation, and society

    53 min

  4. 26 Mar

    Scaling Data in Aviation: Inside Brussels Airlines’ Data Strategy - The Data Playbook Podcast with Kris Peeters & Tom Holsteens

    How do you transform a broken data landscape into a scalable, self-service data platform? In this episode of The Data Playbook, Kris Peeters sits down with Tom Holsteens to unpack how Brussels Airlines rebuilt their data foundation from the ground up. Coming out of the pandemic, the organisation faced a classic problem: 👉 A “spaghetti” data warehouse 👉 No ownership of data assets 👉 A central team becoming the bottleneck What followed was a multi-year transformation focused on: Building a modern cloud data platformMoving to a data product architectureEnabling self-service analytics across teamsBalancing central governance with decentral ownershipLeveraging AI tools to empower non-technical users💡 You’ll learn: Why most data platforms fail (and how to fix them)How to introduce data ownership in business teamsThe real difference between controlling vs. BIHow to reduce bottlenecks with hub-and-spoke modelsA real use case: cutting food waste by 30% with dataWhy perfect data quality is a mythThis is a must-watch for data leaders, engineers, and anyone scaling data in complex organisations. 👉 Subscribe for more episodes: https://www.youtube.com/@Dataminded 👉 Listen on Spotify: https://open.spotify.com/show/your-podcast-link 👉 Explore more content & insights: https://dataminded.com Struggling with data bottlenecks, unclear ownership, or slow delivery? 👉 Explore our Data Product Workshop: https://www.dataminded.com/what-we-do/data-product-workshop Turn your data landscape into a business accelerator with a shared framework, clear ownership, and hands-on guidance in just one day. Chapters 00:00 Introduction & Brussels Airlines context02:30 What is controlling vs. business intelligence?06:00 The problem: “spaghetti” data warehouse & bottlenecks12:30 The transformation: platform, operating model & group strategy19:00 Hub-and-spoke model & self-service analytics27:30 Data products & the “restaurant” analogy35:30 AI, data analysts & scaling data adoption43:30 Real impact: reducing waste & driving business value

    1hr 1min

  5. 16 Mar

    Machine Learning in Energy: Forecasting, MLOps, and Business Impact - The Data Playbook Podcast with Kris Peeters & Jean-Michel Begon

    How do you move machine learning from notebook experiments to production in a real business environment? In this episode of The Data Playbook Podcast, Kris Peeters sits down with Jean-Michel Begon, Senior Machine Learning Engineer at Luminus, to explore how machine learning models are built and operationalized inside an energy company. They discuss electricity demand forecasting, the machine learning lifecycle, model experimentation, industrialisation, monitoring, collaboration with IT, and the role of GenAI and LLMs in modern ML teams. You’ll hear practical lessons on: production machine learningML team structureforecasting model developmentdata pipelines and platform supportmodel monitoring and performance reviewbalancing business value with technical rigorExplore the full podcast series: The Data Playbook PlaylistDiscover more podcasts, blogs, and webinars: Dataminded ResourcesVisit the Dataminded website: https://www.dataminded.com/

    55 min

  6. 29 Jan

    How Dataminded Was Built: Kris Peeters on 11 Years of Data Engineering & Culture - The Data Playbook podcast with Kris Peeters & Pascal Brokmeier

    In this season finale of The Data Playbook Podcast by Dataminded, the tables turn: Kris Peeters (Host & Founder of Dataminded) is interviewed by Pascal Brokmeier (guest from the Episode 2 and former colleague). Kris shares the real story behind 11 years of building Dataminded - from the stress of having zero customers, to landing the first project, to scaling from a small team to a company with a leadership layer. We dive deep into what makes an engineering-first culture work: autonomy + responsibility, raising (and protecting) the hiring bar, learning from mistakes, and why timeless engineering practices (Git, CI/CD, testing, monitoring) still matter, no matter the tech hype cycle. If you’re a data leader, data engineer, engineering manager, or founder, this episode is a practical playbook on building a company (and a culture) that can survive and scale. ✅ Subscribe and follow Dataminded for more episodes, deep dives, and real-world data engineering stories. https://www.youtube.com/@Dataminded ✅ Explore The Data Playbook Podcast archive for more conversations on data platforms, data products, AI, and cloud decisions. https://www.dataminded.com/resources/podcast ✅ Want to work with us? Check our open roles or reach out directly. Open vacancies: https://www.dataminded.com/about/join-usOr email: careers@dataminded.comChapters: 00:06 - 11 Years of Dataminded: Why This Story Matters01:54 - Why Kris Founded Dataminded (Engineers First)04:12 - From Zero Clients to the First Big Win07:53 - First Hires & How Culture Was Born11:14 - Git, CI/CD & Why Engineering Discipline Wins15:59 - Growing from 6 to 20: Chaos to Structure23:30 - Autonomy, Trust & Professional Culture35:13 - COVID, Overhead & the Push to 50 People41:13 - How Dataminded Keeps the Hiring Bar High55:59 - Germany, The Netherlands & What’s Next

    1hr 5min

  7. 14 Jan

    How OBI Built a Lean, High-Impact AI Function That Scales - The Data Playbook Podcast with Kris Peeters & Dr. Ruth Janning

    In this episode of The Data Playbook, we sit down with Dr. Ruth Janning, Head of Data Science & AI at OBI, to talk about what actually drives AI impact in real organisations. We break down: Why GenAI hype leads teams in the wrong directionHow to choose between ML, GenAI and agentic AIReal-world retail AI use cases (recommendations, assortment, automation)How a 10-person team delivers outsized business valueAI governance, self-service, templates & AI ambassadors🎧 Listen to more episodes of The Data Playbook for real-world stories on data platforms, GenAI, data products and cloud independence from Europe’s leading data practitioners and leaders. 🌐 More at https://www.dataminded.com/resources and subscribe to our Spotify channel. Watch the full episode on YouTube: https://youtu.be/hzI9VizGyHM

    1hr 14min

  8. 18/12/2025

    S2 E9. Data Science vs Data Engineering: Breaking the Wall - The Data Playbook Podcast with Kris Peeters & Jelena Grujic

    In this episode of The Data Playbook, Jelena Grujic (Dataminded) explains why the divide between data scientists and data engineers still exists and how to finally break it. We dive into real-world conflicts around unit tests, notebooks, production data access, documentation, and overengineered solutions. Jelena shares pragmatic alternatives like data testing, functional pipelines, and purpose-based access that actually work in production. A must-listen for data leaders and practitioners who want fewer debates and better data products. 🎧 Topics include data testing, notebooks, production data, functional programming, and team collaboration. 🎧 Listen to more episodes of The Data Playbook for real-world stories on data platforms, GenAI, data products and cloud independence from Europe’s leading data practitioners and leaders. 🌐 More at https://www.dataminded.com/resources #DataScience #DataEngineering #DataLeadership #DataTeams #DataPlatform #AnalyticsEngineering #DataInProduction #MachineLearning #ModernDataStack #TheDataPlaybook

    1 hr
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About

🎙️ The Data Playbook is a podcast where we aim to build a playbook for data leaders. We do that through a series of interviews with other data leaders, data practitioners and data experts. In each episode, we break down real-world data challenges: from building modern architectures and embracing Data Mesh to navigating cloud sovereignty, we help you make smarter decisions one play at a time.

Information

  • Creator
    Dataminded
  • Years Active
    2025 - 2026
  • Episodes
    28
  • Rating
    Explicit
  • Copyright
    © Dataminded
  • Show Website
    The Data Playbook Podcast

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