#88 “Data Shapes AI, and AI Shapes Data,” Emilie Nenquin on VRT’s Digital Transformation
Send us a textIn this episode, we explore how public media can build scalable, transparent, and mission-driven data infrastructure - with Emilie Nenquin, Head of Data & Intelligence at VRT, and Stijn Dolphen, Team Lead & Analytics Engineer at Dataroots.Emilie shares how she architected VRT’s data transformation from the ground up: evolving from basic analytics to a full-stack data organization with 45+ specialists across engineering, analytics, AI, and user management. We dive into the strategic shift from Adobe Analytics to Snowplow, and what it means to own your data pipeline in a public service context.Stijn joins to unpack the technical decisions behind VRT’s current architecture, including real-time event tracking, metadata modeling, and integrating 70+ digital platforms into a unified ecosystem.💡 Topics include:Designing data infrastructure for transparency and scaleBuilding a modular, privacy-conscious analytics stackMetadata governance across fragmented content systemsRecommendation systems for discovery, not just engagementThe circular relationship between data quality and AI performanceApplying machine learning in service of cultural and civic missionsWhether you're leading a data team, rethinking your stack, or exploring ethical AI in media, this episode offers practical insights into how data strategy can align with public value.
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#87 How to Successfully Integrate AI into Your Business, with Tim Leers (Global Generative & Agentic AI Lead)
Send us a textWhat happens when AI hype collides with enterprise reality? Tim Leers, Global Generative & Agentic AI Lead at Dataroots, pulls back the curtain on what's actually working—and what's not—in enterprise AI deployment today.We begin by examining why companies like Klarna publicly announced replacing customer service teams with AI, only to quietly backtrack months later when quality suffered. This pattern of inflated expectations followed by reality checks has become common, creating what Tim calls "AI theater" – impressive demos with minimal business impact.The conversation tackles the often misunderstood concept of "agentic AI." Rather than viewing it as a specific technology, Tim frames agency as fundamentally about delegated authority – the ability to trust AI systems with meaningful responsibilities. However, this delegation requires contextual intelligence—providing the right data at the right time—which most organizations struggle to implement effectively."Models are commodities, data is your moat," Tim explains, arguing that proprietary business context will remain the key differentiator even as AI models continue advancing. This perspective challenges the conventional wisdom that focuses primarily on model capabilities rather than data infrastructure.Perhaps most valuably, Tim outlines three pillars for successful enterprise AI: contextual intelligence, continuous improvement (designing systems that evolve with changing business contexts), and human-AI collaboration. This framework shifts focus from technology deployment to sustainable business value creation.The discussion concludes with eight practical lessons for organizations implementing generative AI, from avoiding the temptation to build proprietary models to recognizing that teaching employees to prompt effectively isn't sufficient for enterprise-wide adoption. Each lesson reinforces a central theme: successful AI implementation requires designing for change rather than building rigid systems that quickly become obsolete.Whether you're a technical leader evaluating vendor claims or a business executive trying to separate AI reality from fantasy, this episode provides the practical guidance needed to move beyond the hype cycle toward meaningful implementation.
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#86 What’s Next for Kubernetes? KubeCon 2025 Recap with Nick Schouten
Send us a textWelcome to the cozy corner of the tech world! Datatopics is your go-to spot for relaxed discussions around tech, news, data, and society.In this episode of Data Topics, we sit down with Nick Schouten — data engineer at dataroots — for a full recap of KubeCon Europe 2025 and a deep dive into the current and future state of Kubernetes.We talk through what’s actually happening in the Kubernetes ecosystem — from platform engineering trends to AI infra challenges — and why some teams are doubling down while others are stepping away.Here’s what we cover:What Kubernetes actually is, and how to explain it beyond the buzzwordWhen Kubernetes is the right choice (e.g., hybrid environments, GPU-heavy workloads) — and when it’s overkillHow teams are trying to host LLMs and AI models on Kubernetes, and the blockers they’re hitting (GPUs, complexity, cost)GitOps innovations spotted at KubeCon — like tools that convert UI clicks into Git commits for infrastructure-as-codeWhy observability is still one of Kubernetes’ biggest weaknesses, and how a wave of new startups are trying to solve itThe push to improve developer experience for ML and data teams (no more YAML overload)The debate around abstraction vs control — and how some teams are turning away from Kubernetes entirely in favor of simpler toolsWhat “vibe coding” means in an LLM-driven world, and how voice-to-code workflows are changing how we write infrastructureWhether the future of Kubernetes is more “visible and accessible,” or further under the hoodIf you're a data engineer, MLOps practitioner, platform lead, or simply trying to stay ahead of the curve in infrastructure and AI — this episode is packed with relevant insights from someone who's hands-on with both the tools and the teaching.
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#85 From CDO to author: Jackie Janssen on the evolution of AI and implications for business and society
Send us a textWelcome to the cozy corner of the tech world! Datatopics is your go-to spot for relaxed discussions around tech, news, data, and society.This week, co-host Ben is joined by Jackie Janssen, former Chief Data Officer at CM, author of AI: De Hype Voorbij, and an evangelist for pragmatic, human-centered AI. Together, they trace the winding path from early tech roles to enterprise transformation, exploring how AI can actually serve humans (and not just the hype machine).In this episode:Leadership in AI transformation: From KBC to CM, lessons on creating cultural buy-in.Building effective data teams: Why the first hire isn’t always a data engineer.AI governance: What makes a strong AI Council and why CEOs should care.Product and process thinking: How MLOps, data factories, and product mindsets intersect.Agents and autonomy: The future of work with AI teammates, not just tools.The human edge in a machine world: A preview of Jackie’s next book on rediscovering humanity in the age of AI.Curious about Jackie’s take on AI agents, cultural inertia, or what really makes a great data strategy tick? Tune in, you might just find a new way to think about your tech stack and your team.
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#84 Let’s Get Meta: Why the Metadata You Ignore Might Be Costing You - with Special Guest Corentin
Send us a textWelcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics Unpluggedis your go-to spot for relaxed discussions around tech, news, data, and society.Dive into conversations that should flow as smoothly as your morning coffee (but don’t), where industry insights meet laid-back banter. Whether you're a data aficionado or just someone curious about the digital age, pull up a chair, relax, and let's get into the heart of data—unplugged style!In this episode, we dig deep into a concept everyone pretends to understand: metadata. Joined by our guest Corentin, we unpack what it really means, why it’s more than just “data about data,” and how to make metadata management less of a formality and more of a value driver.Expect hot takes, real-world metaphors, and zero tolerance for shelfware strategies as we cover:Defining metadata: Beyond the buzzphrase, into systems thinkingMetadata vs. data governance: Why this split often misses the pointShop-floor pragmatism: What lean thinking brings to metadata workflowsCommon traps: Like starting with tools instead of actual pain pointsDriving value: From tribal knowledge to structured, sustainable processesWhether you're managing a data platform or just wondering why your data catalog feels like a graveyard, this one’s for you.
About DataTopics Unplugged: All Things Data, AI & Tech
Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics Unplugged is your go-to spot for relaxed discussions around tech, news, data, and society.Dive into conversations that should flow as smoothly as your morning coffee (but don't), where industry insights meet laid-back banter. Whether you're a data aficionado or just someone curious about the digital age, pull up a chair, relax, and let's get into the heart of data, unplugged style!
Listen to DataTopics Unplugged: All Things Data, AI & Tech, All-In with Chamath, Jason, Sacks & Friedberg and many other podcasts from around the world with the radio.net app
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