DataTopics: All Things Data, AI & Tech

DataTopics

Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics 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!

  1. २९ एप्रि

    #95 GEO vs SEO: The New Battle for Discoverability

    Send us Fan Mail Google still drives most search traffic, but the rules of discoverability are changing fast. Today we sit down with Cyril, a client data partner at Dataroots, to unpack what search engine optimization actually is, why the first results page captures the vast majority of clicks, and how small changes in content clarity can shift who finds you and when. We get practical about classic SEO fundamentals: on-page SEO that makes services crystal clear for the right persona, off-page SEO signals like backlinks that build authority, and the technical SEO basics that quietly decide whether you rank at all. Page speed, mobile-first indexing, and user experience are not “nice to have” anymore, and we talk through how tools like Google Lighthouse can reveal what is slowing a site down and where to focus first. Then we move into the 2026 reality of AI search and generative engine optimization (GEO). If ChatGPT or Google Gemini can answer a question instantly, traffic can drop, but trust can rise if your brand gets cited. We explain how to write content that LLMs can use: add a TLDR summary, include FAQ sections, publish structured documentation where it makes sense, and build real authority across the web through credible mentions. If you care about SEO keywords, AI citations, and turning discoverability into revenue through better funnel data, this one is for you. Subscribe for more, share this with a teammate who owns your website, and leave a review if it helped. What part of SEO or GEO feels most confusing in your company right now?

    ३० मिनिटे

  2. २७ फेब्रु

    #94 Agents Are Rising: Why Data Quality Matters More Than Ever

    Send us Fan Mail Trust collapses fast when a dashboard misleads or an AI agent learns from messy data. We dig into how data quality became business critical—and how to move from reactive fire drills to proactive systems—through real stories from clinical trials and large platforms where a single broken test could escalate to the C‑suite. With Stan and David, we map the shifts driving this moment: AI adoption, rising reliance on metrics, and the urgent need for shared definitions, lineage, and monitoring that let teams find root causes before customers feel the impact. We get practical about agents that actually help. Instead of vague hype, we break down a low‑risk architecture for read‑only, metadata‑aware agents that handle repetitive, high‑leverage tasks: writing dbt documentation, proposing data tests, performing lineage‑driven root cause analysis, and auto‑drafting tickets with queries, diffs, and impact notes. We explain why integrated agents beat copy‑paste prompts, how to add guardrails that limit scope and permissions, and what human‑in‑the‑loop review should look like to build real trust without slowing the work. Expect candid guidance on adoption and observability: two layers of visibility—agent behavior and data quality posture—help teams track costs, measure time to resolution, spot repeating incidents, and choose structural fixes. We also explore buy vs build as platforms begin embedding agent capabilities, and we share a clear starting path for any team: prioritize critical datasets, standardize KPIs and definitions, enable tests, and surface lineage so automation has the context it needs. By the end, you’ll have a blueprint to reduce firefighting, improve stakeholder confidence, and make your AI agents smarter by feeding them cleaner, governed data. If this resonates, follow the show, share with your data team, and leave a review with the one task you’d automate first.

    ३० मिनिटे

  3. १९/१२/२०२५

    #93 The Most Misunderstood AI Statistic of the Year: Lessons from Tech Expo on Hype, Failure, and Innovation

    Send us Fan Mail In our final episode of 2025, we sit down with Tim Van Erum to unpack what really stood out at Tech Expo Amsterdam. Together we revisit the most misunderstood AI statistic of the year, exploring why the “95% of AI projects fail” headline is misleading and how hype versus reality played out across the conference. Tim shares why failure and experimentation are not setbacks but essential drivers of innovation, and we highlight Reddit’s Scaling Safety strategy as a powerful example of machine learning in action. This candid conversation closes out the year with lessons on what AI truly delivered in 2025.

    १ तास

  4. ०१/१२/२०२५

    #92 AI in the Newsroom: Building GenAI tools for De Standaard, Nieuwsblad, Telegraaf, NRC & more

    Send us Fan Mail We go inside Mediahuis to see how a small GenAI team is transforming newsroom workflows without losing editorial judgment. From RAG search to headline suggestions and text‑to‑video assists, this episode shares what works, what doesn’t, and how adoption spreads across brands. You’ll hear about: Ten priority use cases shipped across the groupHeadline and summary suggestions that boost clarity and speedRAG‑powered search turning archives into instant contextText‑to‑video tools that free up local video teamsThe hurdles of adoption, quality, and scaling prototypes into productionTheir playbook blends engineering discipline with editorial empathy: use rules where you can, prompt carefully when you must, and always keep journalists in the loop. We also cover policies, guardrails, AI literacy, and how to survive model churn with reusable templates and grounded tests. The result: a practical path to AI in media — protecting judgment, raising quality, and scaling tools without losing each brand’s voice. 🎧 If this sparks ideas for your newsroom or product team, follow the show, share with a colleague, and leave a quick review with your favorite takeaway.

    ५० मिनिटे

  5. १३/११/२०२५

    #91 How Kim Smets, VP Data & AI at Telenet, Scales Enterprise AI with Strategy, People, and Purpose

    Send us Fan Mail In this episode of Data Topics, Ben speaks with Kim Smets, VP Data & AI at Telenet, about his journey from early machine learning work to leading enterprise-wide AI transformation at Telenet. Kim shares how he built a central data & AI team, shifted from fragmented reporting to product thinking, and embedded governance that actually works. They discuss the importance of simplicity, storytelling, and sustainable practices in making AI easy, relevant, and famous across the business. From GenAI exploration to real-world deployment, this episode is packed with practical insights on scaling AI with purpose.

    २५ मिनिटे

  6. २३/१०/२०२५

    #90 How To Make AI Deliver Business Impact: Gaelle Helsmoortel on Turning Strategy Into Tangible Results

    Send us Fan Mail In this episode, Gaelle Helsmoortel joins us to discuss how to make AI truly deliver business impact, not just proof of concept. With over 25 years of experience spanning L’Oréal, startup leadership, and her current role at Dataroots, Gaelle shares her approach to turning business challenges into measurable value. She breaks down her proven 5Ps framework (Purpose, People, Process, Platform, and Performance) and explains how companies can bridge the gap between strategy and execution to generate real results. 🎧 You’ll learn: Why most AI projects fail (and how to prevent it)How to move from proof of concept to proof of valueHow to align business purpose, data, and people for maximum impactWhy “purpose before platform” is key to successful AI adoptionWhether you’re a business leader, strategist, or data professional, this episode will help you understand how to make AI work for business and deliver tangible results. 🔗 Connect with Gaëlle: 🌐 Website & Newsletter: Generative Booster – The Game Changer List ▶️ YouTube Channel: @GenerativeBooster

    ३० मिनिटे
  7. #89 SQLBits Unfiltered: dbt in Fabric, MLOps in Action & Copilot in Question

    २५/०९/२०२५

    #89 SQLBits Unfiltered: dbt in Fabric, MLOps in Action & Copilot in Question

    Send us Fan Mail In this episode, we're joined by Sam Debruyn and Dorian Van den Heede who reflect on their talks at SQL Bits 2025 and dive into the technical content they presented. Sam walks through how dbt integrates with Microsoft Fabric, explaining how it improves lakehouse and warehouse workflows by adding modularity, testing, and documentation to SQL development. He also touches on Fusion’s SQL optimization features and how it compares to tools like SQLMesh. Dorian shares his MLOps demo, which simulates beating football bookmakers using historical data,nshowing how to build a full pipeline with Azure ML, from feature engineering to model deployment. They discuss the role of Python modeling in dbt, orchestration with Azure ML, and the practical challenges of implementing MLOps in real-world scenarios. Toward the end, they explore how AI tools like Copilot are changing the way engineers learn and debug code, raising questions about explainability, skill development, and the future of junior roles in tech. It’s rich conversation covering dbt, MLOps, Python, Azure ML, and the evolving role of AI in engineering.

    १तास २१मि.
  8. #88 “Data Shapes AI, and AI Shapes Data,” Emilie Nenquin on VRT’s Digital Transformation

    ११/०९/२०२५

    #88 “Data Shapes AI, and AI Shapes Data,” Emilie Nenquin on VRT’s Digital Transformation

    Send us Fan Mail In 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.

    ५३ मिनिटे
सर्व पहा (९५)

ह्याविषयी

Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics 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!

माहिती

  • निर्माता
    DataTopics
  • सक्रिय वर्षे
    २०२२ - २०२६
  • एपिसोड्स
    ९५
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    क्लीन करा
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    DataTopics: All Things Data, AI & Tech