Explicit Measures Podcast
Hosted by Mike Carlo, and Tommy Puglia, the Explicit Measures Podcast is a Power BI focused show that is like being around a Power BI Pro’s Water Cooler. With so many available resources in the community that focuses on the “how” in Power BI (how to do Drill Through, how to use DAX, etc.,), the Explicit Measures Podcast is all around the WHY. Why use a particular feature, does it make sense for my users? Build the toolset, learn the how, and then come to the Podcast to the listen to the why in situations we all experience as Power BI Pros.
Episodes
Mike & Tommy tackle the hub-and-spoke composite model pattern, weighing in on whether splitting a bloated golden semantic model into a core hub with department-specific spokes delivers real simplification or just trades one problem for another. Prompted by Austin's question about avoiding a 100+ table behemoth, they break down what belongs in the hub, where DirectQuery connections start to hurt, and what governance guardrails t...
Mike & Tommy dive into the 2026 Gartner Magic Quadrant for Analytics and BI, breaking down what Microsoft's 19th consecutive Leader recognition actually means in an era where every vendor claims to be AI-first. They explore whether the real story is Power BI, Fabric, or the broader Microsoft ecosystem, and tackle the central tension of whether AI is making BI more powerful or just more confusing. Tune in for a practical take on...
Mike & Tommy tackle a question every data team manager is wrestling with: should junior staff learn DAX fundamentals before touching agentic AI tools, or can they dive straight in? Drawing from a listener in the insurance industry who manages a data team, they explore the tension between building real technical depth and embracing AI-assisted efficiency, and whether letting juniors "vibe DAX" creates dangerous blind spots or a ...
Mike & Tommy tackle the uncomfortable truth about AI-generated data pipelines — how code that looks clean and runs without errors can still deliver confidently wrong results. Drawing from this article, they explore why silent failures in joins, filters, and business rules are harder to catch than broken code, and what Power BI and Fabric teams must do to validate outputs before bad data reaches their reports.
Mike & Tommy dive into Microsoft's RayFin, weighing in on whether this new code-first app experience inside Fabric is a genuine shift in how teams deliver data insights — or just another layer of hype. They explore the tension between RayFin and Power BI reports, tackle who actually owns these apps in the enterprise, and break down what BI professionals should do right now before the next wave hits.
Mike & Tommy dive into why data literacy might be missing its most important lesson — not how to read a chart, but how to question the story it's telling. Drawing from a Nightingale article on graph literacy and self-skepticism, they explore whether polished dashboards are quietly building cultures of data compliance over data curiosity.
They break down how motivated skepticism, biased interpretation, and over-trusted KPIs...
Mike & Tommy tackle whether AI agents can solve what the Power BI admin portal can't—giving you a true tenant-level, workspace-free view of who can access what in Fabric. They break down Taylor B.'s real-world agent that stitches together audit logs, model APIs, grants, direct links, and app audiences into a central governance store, and weigh in on whether Microsoft's native governance story is ready or still a DIY puzzl...
Mike & Tommy tackle the often-overlooked "outer context" problem in agentic Fabric development — exploring why request tracking systems like Notion, GitHub Issues, or even ADO matter more than most teams realize, and how building a proper project harness could be the difference between an agent that delivers and one that drifts.
They break down how to map these workflows across corporate tool stacks — Loop, OneNote, ...
Mike & Tommy tackle the surprisingly tricky problem of tracking Power BI app usage at scale, exploring why app-level telemetry is harder to surface than report-level metrics and how teams can map usage back to districts using Entra ID, Admin APIs, and audit logs.
They break down which telemetry sources are actually viable, how to avoid common pitfalls like audience filters hiding true reach and shared devices skewing counts, and...
Mike & Tommy tackle why organizations are still dragging their feet on AI adoption even with Microsoft Fabric sitting right in front of them — weighing in on whether the real blockers are skills, data quality, governance, or just unclear ROI.
They break down what "AI-ready" actually looks like in a Fabric and Power BI environment, how to tell AI strategy from AI theater, and what a realistic 30/60/90-day plan looks like to...
Mike & Tommy tackle the question of whether it's time to hold CEOs and CFOs accountable for data literacy, not just the analysts building the reports. Inspired by a mailbag from jedc at bi.fo, they explore why leaders so often ask for A when the business actually needs B, and what it really takes to build a shared data language across the org.
They also cover the latest on AI-powered Power BI reporting from design to deployment:...
Mike & Tommy dive into the second half of the AI self-service analytics story, tackling governance, skills, and validation — and why giving everyone the ability to ask questions of data raises the stakes, not just the speed.
They break down what a "Skill" actually means in Power BI terms, who owns the wrong answer when Claude writes the query, and how BI teams can build validation checkpoints that create trust without grin...
Mike & Tommy dive into self-service analytics with AI, exploring how tools like Claude are changing the way business users interact with data — and whether speed and access come at the cost of trust and governance.
They break down what semantic models need to look like when chat is the primary interface, who owns accountability when AI gives a wrong answer, and what practical guardrails BI teams should put in place before ...
Mike & Tommy tackle the growing tension between individual and team-owned Microsoft Fabric Agent Skills, exploring how BI teams should organize, govern, and promote skills without killing innovation or creating shadow BI.
They break down the full skill lifecycle — from personal experiments to certified team assets — and land on practical governance guardrails that are lightweight enough to actually stick.
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Mike & Tommy tackle whether Power BI developers are quietly becoming professional QA testers in the age of Microsoft MCP, weighing in on what separates a true senior developer from a junior when AI writes the first draft.
They explore how the developer role is shifting, who owns accountability when AI-generated measures ship broken, and what skills still matter when the tool can do the typing.
More on Microsoft MCP for Power BI: ...
Mike & Tommy dive into RayFin, Microsoft's new AI-first product for building, deploying, and governing agents inside Microsoft Fabric, exploring whether this is a true shift in how BI teams work or just another layer of hype on day one.
They break down what RayFin actually changes for semantic models, reports, and pipelines, tackle the real governance risks when AI can build and deploy at platform speed, and land on the practica...
Mike & Tommy dive into Microsoft Build 2026, breaking down what the "agentic apps" announcement actually means for Power BI and Fabric teams—and whether this is a real architecture shift or just rebranded copilots.
They weigh in on how Fabric Data Factory orchestration, Microsoft Databases, and Agent Skills change the day-to-day for BI developers and data engineers, and what governance guardrails teams need before anything...
Mike & Tommy dive into CI/CD automation with agents in Microsoft Fabric, exploring how agentic workflows are reshaping deployment pipelines, whether AI-driven deployments introduce more speed or more risk, and what guardrails teams need before letting agents touch production workspaces.
Mike & Tommy dive into Claude Design meets Power BI Embedded, exploring whether AI-generated UX is a shortcut or a quality risk, how semantic models stay the source of truth when LLMs scaffold embedded apps, and what guardrails belong on every AI-assisted analytics project.
https://www.reddit.com/r/PowerBI/comments/1sy5kue/claude_design_meets_power_bi_embedded/
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Mike & Tommy tackle Microsoft Fabric hints to work faster, exploring whether teams are wasting time due to self-inflicted bad workflows, poor reuse, and confusing busy work with shipping value. They break down which repeatable tasks should be standardized first, when "just build it" becomes technical debt, and what practical Fabric habits listeners can adopt this week to stop the waste and start delivering faster.
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