The Data Playbook Podcast

Dataminded
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🎙️ 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. 1 天前

    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 分鐘

  2. 3月26日

    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

    1 小時 1 分鐘

  3. 3月16日

    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 分鐘

  4. 1月29日

    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

    1 小時 5 分鐘

  5. 1月14日

    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

    1 小時 14 分鐘

  6. 2025/12/18

    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 小時

  7. 2025/12/11

    S2 E8. A Structured Framework for Building Successful Data Solutions - The Data Playbook Podcast with Kris Peeters & Frederic Vanderveken

    Most data leaders know the statistic: the majority of big data initiatives never deliver the value they promised. In this episode, Kris sits down with Frederic Vanderveken from Dataminded to unpack a practical framework to choose and validate the right data use cases. We cover: Why so many data initiatives fail before they even startHow to anchor your work in business strategy, not technologyHow to run problem discovery interviews that surface real headaches, not minor annoyancesPrioritising solutions using five lenses: customer, growth, money, pragmatic feasibility and differentiatorsBuilding a quantifiable business case and defining success upfrontIf you’re a data leader or product owner deciding where to place your next big bet, this episode gives you a structured way to reduce risk and ship data solutions that actually move the needle. Follow The Data Playbook for more episodes on data platforms, data products and making AI useful in real life. 🌐 More at ⁠www.dataminded.com⁠ and subscribe to our channel. ⏱️ Chapters: 00:00 Introduction to Data Solutions Framework09:03 Effective Problem Discovery Techniques17:53 Mapping Customer Journeys26:39 Collaborative Solution Brainstorming32:27 Testing Solutions and Integration44:39 Final Thoughts and Key Takeaways

    47 分鐘

  8. 2025/11/27

    S2 E7. Data Engineering Meets Excel: Building Explainable and Reliable Decision Models with River Solutions

    Kris Peeters sits down with Amaury Anciaux, founder of River Solutions, to tackle a painful reality for data leaders: critical decisions still depend on fragile Excel models. They explore why Excel won’t disappear, how River turns spreadsheets into visual, explainable and reliable decision models, and what happens when you bring data quality checks, testing and documentation into the analyst workflow. Topics include: Why 99% of models in organisations are still built in ExcelSilent errors, risk, and the real cost of debugging formulasVisual flow-based modelling and model maps inside ExcelBuilt-in checks for missing data, duplicates and broken lookupsHow AI copilots helped build River, and why AI won’t replace transparent modelsThe evolving role of analysts and managers in data-driven decisions🎧 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 Chapters: 00:00 – Intro & episode setup00:45 – Amaury’s background & consulting career02:00 – The hidden reality of Excel decision models04:00 – Why “just get it out of Excel” doesn’t scale05:10 – What River Solutions does in Excel06:40 – Visual model maps for explainable models08:40 – Removing formulas & adding data quality checks10:50 – Why Excel errors are so risky for big decisions13:15 – Who River is for: analysts, Excel gurus & managers16:05 – Why Amaury started River now & building with Copilot19:00 – Will AI copilots replace River and Excel modelling?22:51 – How River works as an Excel add-in (UX & interactivity)26:25 – How River changes the analyst role (less debugging, more thinking)28:10 – Roadmap: community, cloud, AI & connecting to data warehouses31:14 – Biggest lesson learned: software is easy, change is hard

    32 分鐘
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簡介

🎙️ 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.

資訊

  • 創作者
    Dataminded
  • 活躍年代
    2025年 - 2026年
  • 集數
    26
  • 年齡分級
    兒少適宜
  • 版權
    © Dataminded
  • 節目網站
    The Data Playbook Podcast

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