Explicit Measures Podcast

The conversation explores how AI and Microsoft Fabric are reshaping the traditional report developer role. They debate semantic modeling versus lakehouse approaches for ML and data science. The hosts compare paginated, pixel-perfect exports with interactive Power BI visuals and discuss when each is needed. Practical hiring lenses and day-to-day responsibilities for modern BI teams are examined.

Mike & Tommy weigh in on whether Microsoft Fabric has earned the same trust as Power BI, exploring if it's truly dependable for small businesses and enterprises alike, and examining what trust even means for an all-in-one platform that's still rapidly evolving.https://x.com/gothburz/status/2019539563027247147?s=46&t=A8umCvjDNrtK_1gwT1T7qQhttps://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-ithttps://blog.fabric.microsoft.com/en-us/blog/supercharge-ai-bi-and-data-engineering-with-semantic-link-generally-available/https://powerbi.microsoft.com/en-us/blog/deprecation-of-old-excel-and-csv-import-experience-in-power-bi-service/Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Discussion on how to structure Microsoft Fabric workspaces and tradeoffs of medallion architecture versus deployment complexity. Debate over whether centralized control helps or hinders self-service at scale. Examination of how AI and agents actually increase governance needs and expand work. Practical patterns for workspace placement, access layers, and delegation strategies.

We made it 500! Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Mike & Tommy explore whether being late to the data game is actually an advantage in the AI era, questioning if organizations building fresh Fabric implementations can leapfrog legacy technical debt—or if they're doomed to repeat the same governance mistakes. They tackle Sandra's mailbag question about late adoption, semantic modeling for AI readiness, and when to let ontology "brew" versus act now.Get in touch:Send in your questions or topics you want us to discuss by tweeting to @PowerBITips with the hashtag #empMailbag or submit on the PowerBI.tips Podcast Page.Visit PowerBI.tips: https://powerbi.tips/Watch the episodes live every Tuesday and Thursday morning at 730am CST on YouTube: https://www.youtube.com/powerbitipsSubscribe on Spotify: https://open.spotify.com/show/230fp78XmHHRXTiYICRLVvSubscribe on Apple: https://podcasts.apple.com/us/podcast/explicit-measures-podcast/id1568944083‎Check Out Community Jam: https://jam.powerbi.tipsFollow Mike: https://www.linkedin.com/in/michaelcarlo/Follow Tommy: https://www.linkedin.com/in/tommypuglia/

Hosts warn against buying tools before defining the decision you want to improve. They debate how AI and Fabric change work, discovery, and metadata needs. Practical ideas include AI-assisted data discovery, reusable model views, and breaking problems into tasks agents can run. Discussion also covers governance, privacy, and where personalization fits in modern analytics.

They dig into connecting local VS Code to remote Fabric Jupyter kernels and whether Fabric fits traditional data science workflows. They compare remote kernels, VMs, and local development trade offs. They discuss custom Fabric environments, data movement with OneLake, and how to make notebooks portable between local and remote runs.

Mike and Tommy engage with a listener's critique of Microsoft's excessive use of the term 'experience' in their products. They debate its impact on user expectations and adoption. The duo explores whether clearer language could benefit data teams. They also cover updates in Power BI, from deployment pipelines to the convenience of new features like Azure Maps marker support. The discussion touches on AI's influence on data tasks and the evolving role of natural language in programming, emphasizing the need for meaningful UX over buzzwords.

Mike and Tommy dive into the intricacies of Microsoft Fabric, questioning its necessity and warning against over-provisioning. They explore intriguing case studies revealing significant cost savings by switching to more suitable solutions. The duo also discusses data preparation for Gen AI, the limitations of Azure tools, and the importance of aligning AI capabilities with business needs. With insights on managing skill gaps and cautioning overestimations of Fabric, they provide practical advice for organizations navigating complex tech landscapes.

Mike and Tommy dive into the world of Microsoft's MCP servers and AI agents for Power BI and Fabric. They discuss whether teams should quickly embrace these integrations or proceed with caution. The hosts highlight the critical balance between agent capabilities and the need for human oversight. Listeners will learn how agents can enhance workflows by catching exceptions and organizing data effectively. Security risks and the importance of pilot testing are key concerns, making this an essential listen for anyone involved in data management.