Podcasts about power bi

Arun Parameswaran: Product Owners Who Create Better Product Conversations in Scrum In this episode, we refer to Arun's AI prompt library for Scrum Masters and project managers. The Great Product Owner: Curiosity, Clear Direction, and Outcome Focus Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "A great PO doesn't only ask, did we deliver? They ask, do people communicate openly?" - Arun Parameswaran   Arun describes great Product Owners as collaborative, curious, and close enough to the team to understand how delivery really works. The best POs he worked with did more than check whether items were delivered. They asked whether knowledge was distributed, whether people communicated openly, and whether everyone had a chance to contribute. They gave the team clear product direction, supported prioritization, managed stakeholders, and stayed available when the team needed context. Arun emphasizes outcome focus: value for the customer expressed in a way the team can understand. A strong PO becomes the bridge in both directions, helping stakeholders understand the team and helping the team understand the customer.   Self-reflection Question: Does your Product Owner help the team understand customer value, or only the next ticket? The Bad Product Owner: Turning the Team Into a Ticket Factory Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "The Scrum Master shouldn't just help the PO write better tickets. We should help create better product conversations." - Arun Parameswaran   The anti-pattern Arun warns about is the Product Owner as ticket distributor. Stakeholders ask for something, the PO turns it into a ticket, and the team delivers without understanding the problem, the outcome, or why the work matters. Over time, the team becomes a delivery factory, and Scrum starts to look like waterfall with smaller batches. Arun's coaching move is to shift the conversation away from "better tickets" and toward better product thinking. What problem are we solving for customers? What outcome do we expect? What should we prioritize? What can we say no to? For Scrum Masters, this means coaching the PO and the team to bring customer context, stakeholder feedback, and prioritization into the same conversation.   Self-reflection Question: What product conversation is your team avoiding by hiding behind ticket writing?   [The Scrum Master Toolbox Podcast Recommends]

Arun Parameswaran: Success for Scrum Masters Means Teams Ask Better Questions Without You Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "My goal isn't to become indispensable. My goal is to create a team that doesn't depend on me." - Arun Parameswaran   For Arun, Scrum Master success is not measured by how many meetings he runs or how often the team asks him for help. It is measured by the team's ability to solve problems without depending on him. If he has to remind everyone to update Jira, facilitate every difficult conversation, or resolve every obstacle, he is creating dependency. A healthier signal is when team members talk directly to each other: "This is blocked. Who can help me?" or "Let's finish this before starting something else." Arun compares the Scrum Master to a football coach watching the match from the side. The team needs space to play, make decisions, and learn. The Scrum Master still observes and coaches, but the goal is to intervene less often and more intentionally. As Vasco summarizes, this requires learning to wait before stepping in.   Self-reflection Question: What would your team do differently if you waited one more minute before intervening? Featured Retrospective Format for the Week: What? So What? Now What? Arun's favorite retrospective format is "What? So What? Now What?" because it moves the team from facts to meaning to action. "What happened?" helps the team describe reality. "So what?" asks why it matters. "Now what?" turns the discussion into a small experiment for the next sprint. Arun also avoids using the same format every time. He often shares the board two or three days before the retrospective so people can reflect before the meeting, add observations, and appreciate teammates. That preparation saves time in the session and makes space for a short fun activity before the team works through the real topics. His goal is simple: every retrospective should produce learning and at least one concrete experiment.   [The Scrum Master Toolbox Podcast Recommends]

Arun Parameswaran: Using Scrumban and WIP Limits to Help Agile Teams Find Focus Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "The WIP limit helped the developers not context switch." - Arun Parameswaran   Arun brought a practical challenge to the Wednesday coaching conversation: a team doing both operations and development work needed more visibility and focus than their Scrum board was giving them. The trigger was context switching. Work stayed "in progress" even when blocked, people picked up new topics before finishing old ones, and stakeholders kept asking what was actually happening. Arun helped the team experiment with Scrumban, keeping useful Scrum events while adding a Kanban-style board and explicit WIP limits. The breakthrough was not just visualizing the work. It was helping the team own the limits. They created an "operator of the week," rotating the responsibility for watching WIP and calling out when the team was taking on too much. That small practice made focus a team responsibility instead of a Scrum Master lecture.   Self-reflection Question: Who owns your team's WIP limits in practice, not just on the board?   [The Scrum Master Toolbox Podcast Recommends]

Arun Parameswaran: How Powerful Questions Help Scrum Teams Handle Stakeholder Conflict Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "Sometimes the best thing a Scrum Master can give the team isn't the answer. It's a question." - Arun Parameswaran   Arun describes a team pattern many Scrum Masters recognize: stakeholders bypassing the Product Owner and going straight to developers with new requests after the sprint had already started. The developers wanted to help, so they accepted the interruptions. The result was context switching, broken priorities, and a quiet loss of focus. Arun worked with the customer team, Product Owner, and developers to create a simple agreement: new work had to come through the PO, be clarified, and be prioritized before it reached the team. That agreement gave developers permission to protect the sprint without turning every conversation into a personal conflict. Arun also shares how he handled the classic misunderstanding that "being Agile" means accepting every change immediately. For him, adaptability still needs timing, clarity, and shared agreements.   In this segment, we talk about the coaching stance and how Scrum Masters can use questions to help teams think together.   Self-reflection Question: What agreement would help your team protect focus without shutting stakeholders out? Featured Book of the Week: Coaching Agile Teams by Lyssa Adkins Arun recommends Coaching Agile Teams by Lyssa Adkins because it helped him move beyond ceremony facilitation. The book gave him a clearer picture of the Scrum Master as a coach for individuals, the team, and the wider organization. One question stayed with him: am I solving the problem for the team, or helping the team learn to solve it themselves? That shift changed how Arun worked. Instead of telling teams what to do, he began asking questions such as "What do you think is causing this?", "What options do we have?", and "What are we not seeing?" For Arun, the book is a practical reminder that coaching is not about leading people to your answer. It is about helping people think.   [The Scrum Master Toolbox Podcast Recommends]

Arun Parameswaran: The Scrum Master Mistake of Fixing Trust With Process Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "Don't confuse activity with progress." - Arun Parameswaran   When Arun Parameswaran stepped into one of his first Scrum Master assignments, he joined a distributed team where everything looked normal from the outside. Meetings were happening, Jira was updated, and work appeared to be moving. Underneath that surface, knowledge was unevenly shared, communication between locations was weak, and trust was not yet strong enough for people to speak openly. Arun's first instinct was to add more structure: more meetings, more activities, more process. Looking back, he saw the real mistake. He was creating activity, not progress. The shift came when he stopped trying to provide answers and started listening through one-on-one conversations. He learned where people were struggling, what they expected from him, and what the team needed to own for itself. In this episode, Arun shares why Scrum Masters must understand people before changing the process, and why the best coaching often starts by asking better questions.   Self-reflection Question: Where are you adding process today because the real issue feels harder to talk about?   [The Scrum Master Toolbox Podcast Recommends]

Mike & Tommy dive into the emerging pattern of Fabric as a Backend (FaaB), exploring whether Fabric is becoming the default way teams think about their entire data ecosystem or just a front-facing adoption tool.They weigh in on whether this pattern is a natural evolution of the platform or a case of forcing an analytics engine into an operational role — and what guardrails teams need before going all in.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/

For most of tech history, the new thing belonged to the new people. Then AI showed up and ruined a perfectly good pattern. Because the smartest model on the planet can know darn near everything and still have no idea how your company works. It doesn't know which rules matter, which ones everyone ignores, why that ugly spreadsheet still exists, or that the "temporary" workaround from 2019 is now apparently infrastructure. Jon Perl, Tim Rodman, and Trent McKinster join Rob for a conversation about Fair Game that pretty quickly becomes a conversation about who has the upper hand here. And it might just be the crafters. The people who spent years poking at problems, pulling things apart, building better ways to do the work, and collecting the kind of business context you can't download with a model. From there, things get wonderfully nerdy. Custom AI. Semantic models getting their long overdue victory lap. Whether SaaS is about to get picked apart one annoying subscription at a time. And the possibility that we've been thinking about the AI skills gap completely backwards. Maybe experience isn't the thing AI replaces. Maybe it's the thing AI has been waiting for.

Wenn Controller auf der Datenplattform rumpfuschen, kriegen Datenarchitekten normalerweise Schnappatmung. Was passiert aber, wenn das Controlling selbst die Machete in die Hand nimmt und die Datenplattform einfach selbst aufbaut?In dieser Folge von UNF#CK YOUR DATA spricht Dr. Christian Krug mit Thomas Brenner, Projektcontroller bei den GROB-Werken (10.000 Mitarbeiter; 1,8 Mrd. € Umsatzerlös). Thomas erzählt ungefiltert, wie sie den Absprung vom veralteten SAP BW geschafft haben, warum Snowflake am Ende zu technisch fürs Business war und wie sie mit Microsoft Fabric & Power BI 250 verbuggte Einzelberichte in ein einziges zentrales "Golden Model" verwandelt haben.In dieser Folge lernst du:

Mike & Tommy dive into what agentic development actually means for Power BI teams, breaking down the crawl, walk, run framework for safely adopting AI agents across BI assets. They explore why the shift goes far beyond Copilot prompts, how semantic models become the center of the conversation, and whether most orgs are ready to trust agents with DAX, RLS, and report generation. Tune in for a practical roadmap on where to start, what guardrails are non-negotiable, and how experienced pros stay relevant as agents take on more of the build.Read the article: https://datasavvy.me/2026/06/22/crawl-walk-run-with-agentic-development-of-power-bi-assets/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/

What if the biggest threat to your healthcare organization isn't competition or reimbursement rates — it's the moment one of your team members decided that the policy was more important than the person in front of them? In this episode, Jamie sits down with Matt Staub, CEO of Your Health, to explore the timeless "Give 'Em the Pickle" philosophy — born in a burger joint, but almost perfectly designed for healthcare. Matt and Jamie unpack the four pillars of the pickle framework — service, attitude, consistency, and teamwork — and trace each one directly into the reality of patient care, care team dynamics, and organizational culture. Video LinkGive Em The Pickle Youtube Video   What you'll hear in this episode: Why charging a loyal customer 75 cents for extra pickles is the same mistake healthcare makes every day — and how the Ritz Carlton's $2,500 employee empowerment policy points to a better way How attitude isn't just a soft skill — it's the infrastructure of every patient interaction, including the ones where you're already having a bad day Why mistakes in healthcare aren't failures — they're invitations, and the patients who complained and felt heard often become your fiercest advocates What real consistency looks like in care delivery: not doing the same thing robotically, but doing ordinary things extraordinarily well, every single time How teamwork in healthcare means every person in the organization — from the CEO to the community health worker — has a role in whether the patient feels seen and served This episode will challenge you to look at service not as a department or a satisfaction score, but as the very soul of what your organization stands for. Give 'em the pickle.

Can EHS transition from a cost center into a strategic business driver that protects the bottom line? In this episode of the MuuvWell Podcast, host Kevin sits down with Ryan Rouse (CSP), EHS Manager at Vybond in Franklin, Kentucky. Drawing from 10 years at General Motors and 7.5 years scaling safety operations at Amazon, Ryan breaks down how he applies enterprise-level systems to modern manufacturing.Discover how Vybond tackled soft tissue injuries—which previously accounted for over 54% of their recordable incidents—by establishing an innovative on-site injury prevention clinic covering both workplace and personal health at zero cost to workers. Ryan also shares how he eliminated expensive standalone EHS software, leveraging native Microsoft Power Automate tools to automate near-miss tracking and spend 50% of his team's time out on the plant floor.Key Takeaways:Lessons from GM & Amazon: Applying scalable mechanisms from enterprise environments to modern manufacturing facilities.Merging Personal Health & Ergonomics: How providing on-site physical therapy for personal physical issues lowers overall health insurance costs and prevents workers' comp claims.A New Safety Standard: Shifting from "go home in the same condition" to "go home feeling better than when you arrived."Consolidating EHS Tech Stacks: Replacing costly standalone EHS software with native Microsoft Power Automate, Power Apps, and Power BI integrated directly into operations.The 5-Level Near-Miss System: Prioritizing near-miss reporting into five distinct levels to automate follow-ups and eliminate spreadsheet tracking.Connect with MuuvWell:

La Escuela de Artes y Oficios de la UNSE abrió las inscripciones para el curso Power BI Inicial, a cargo del capacitador Juan Carlos Borges Pons.La propuesta se desarrollará de manera virtual, durante dos meses, con clases los lunes de 15 a 18 horas.Durante la capacitación, los participantes podrán introducirse en el mundo del análisis de datos y aprender a utilizar herramientas que permiten transformar información en reportes y tableros útiles para la toma de decisiones.Las inscripciones se encuentran abiertas a través de la Escuela de Artes y Oficios de la UNSE.

Mike & Tommy dive into the Power BI Desktop Bridge preview, exploring how this new local API surface lets external tools and AI agents interact directly with a running Desktop session — and whether that changes report authoring forever.They break down the Report Authoring Skill showcase, weigh in on the governance risks of agent-driven edits outside of source control, and discuss what experienced teams should actually test before trusting an edit–verify loop with their models.Read more: https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Power-BI-Desktop-Bridge-Preview/ba-p/5227769Get 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/

In this episode of Future Finance, hosts Paul Barnhurst and Glenn Hopper welcome Robert Collie to discuss artificial intelligence, data analytics, and the future of work. Robert shares his journey from helping build Power Pivot and Power BI at Microsoft to founding P3 Adaptive. He explains how AI is changing the role of finance and data professionals, why strong data foundations still matter, and why continuous learning is essential in an AI-driven world.Robert Collie is the founder and CEO of P3 Adaptive, a Microsoft analytics and AI consulting firm. During his 13 years at Microsoft, he helped lead the development of Power Pivot and Power BI. He is also the author of Power Pivot and Power BI and the upcoming book Fair Game: Customizing AI to Your Business Is Easier Than You Think. In this episode, you will discover:How Power Pivot and Power BI transformed data analytics.Why AI is creating new opportunities for finance professionals.Why adapting skills is critical in the AI era.How businesses can make AI practical and accessible.Robert shares practical insights on combining data expertise, AI, and human judgment to create value in the future of work. Follow Glenn:LinkedIn: https://www.linkedin.com/in/gbhopperiiiFollow Paul:LinkedIn: https://www.linkedin.com/in/thefpandaguyFollow Robert:Website: https://p3adaptive.com/Book: https://fairgamebook.ai/LinkedIn: https://www.linkedin.com/in/robcollie/In Today's Episode:[03:58] - Building Power Pivot and Power BI at Microsoft[08:56] - Leaving Microsoft and Founding P3 Adaptive[13:36] - AI and the Future of Work[17:13] - Introducing Fair Game[19:41] - Making AI Practical and Accessible[21:31] - Helping Everyone Understand AI

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 teams need before scaling this architecture.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/

Nadia Ness is Executive Director of Transformation at the University of Glasgow. Our conversation covers a wide range of topics about prioritising and leading change across the University, and the focus that Nadia places on people and partnership to deliver change well. With the earlier part of her career having been in senior roles in the corporate sector, including at Ikea, we also reflect upon the similarities and differences between that environment and leading change in HE. And on the theme of change and transformation, we additionally take a brief detour to talk about Nadia's recent experience of stepping out of the workplace for a period of maternity leave, and some of the perspectives on change that she has since brought back. This episode is brought to you by SEAtS, the Education Operations Platform trusted by universities, colleges, and education providers worldwide. If your timetabling, attendance, compliance, and campus operations are spread across multiple systems, SEAtS brings them together on one AI-powered platform built on Microsoft Azure and natively integrated with Microsoft Teams and Power BI. From day one, it's audit-ready and designed to simplify operations while improving student engagement and institutional performance. Leading institutions have increased retention by up to 20%, protecting millions in tuition revenue while helping thousands more students stay on track. To start a pilot or discuss your requirements, visit seatsone.com. The Association of Higher Education Professionals and the British Universities FInance Directors Group, BUFDG, are both proud to support Job Shadowing HE as a valuable source of professional insight.

This week: Microsoft and Amazon both reported quarterly numbers, and both stocks rose on cloud results that beat expectations. Is AI spending is paying off in real business? And in related news, Microsoft sees a rare annual headcount decline, hitting product R&D hardest. Plus: Satya Nadella builds a Power BI dashboard out of an analyst's research report, and touts it on the earnings call to make a bigger point. Jeff Bezos names Amazon's chips business as the long-awaited fourth pillar. And AI House managing director Jacob Colker delivers a much-needed pep talk for Seattle tech, calling on the region to recognize and build on its strengths. With GeekWire co-founders Todd Bishop and John Cook. Related stories and links: Microsoft and Amazon earnings Microsoft Azure tops $100B in annual revenue as record AI spending cuts into cash flow AWS is 'booming,' but Amazon's free cash flow turns negative on record AI spending Microsoft R&D jobs drop for second straight year as total headcount falls for first time in a decade Which Microsoft businesses are growing and shrinking, according to obscure table in regulatory filing Amazon's fourth pillar Jeff Bezos says this business is becoming Amazon's next 'pillar' A rallying cry for Seattle tech Watch: A venture capitalist's passionate speech, a rallying cry, really, about Seattle Seattle's AI2 Incubator rebrands as AI House, and adds key investor as managing director 'I'm tired of that narrative': Seattle VC pushes back on tech exodus talk The Washington tech ecosystem New map traces Washington state's tech 'universe' to a few key hubs, and shows what's at risk After hiring AWS exec and raising $107M seed round, Virginia startup plants flag in Seattle area GeekWire's Seattle engineering centers list See omnystudio.com/listener for privacy information.

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 what data teams should do differently before letting agents answer business questions.https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/Microsoft-named-a-Leader-in-the-2026-Gartner-Magic-Quadrant-for/ba-p/5262403https://www.gartner.com/doc/reprints?id=1-2NLYXIAL&ct=260626&st=sbGet 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/

In this episode of Future Finance, hosts Paul Barnhurst and Glenn Hopper welcome Robert Collie, founder and CEO of P3 Adaptive, for a conversation about artificial intelligence, data analytics, and how finance professionals can prepare for the future of work. Robert shares his journey from helping build Power BI at Microsoft to founding P3 Adaptive and explains why AI is creating both disruption and new opportunities for finance and data professionals.Robert Collie is the founder and CEO of P3 Adaptive, a Microsoft analytics and AI consulting firm. During his 13 years at Microsoft, Robert helped lead the development of Power Pivot and Power BI. He is also the author of the bestselling Power Pivot and Power BI book and hosts the Raw Data with Rob Collie podcast. His upcoming book, Fair Game: Customizing AI to Your Business is Easier Than You Think, explores how organizations can make AI practical and accessible.In this episode, you will discover:How Power BI and Power Pivot changed the way organizations use data.Why AI is creating new opportunities for finance and data professionals.Why sitting still with current skills can create career risks.How companies can build AI systems using strong data foundations.Why semantic models are becoming essential for AI adoption.Robert brings decades of experience in business intelligence, analytics, and AI, sharing practical lessons on how finance leaders and data professionals can adapt, learn, and create value in a rapidly changing environment.Follow Glenn:LinkedIn: https://www.linkedin.com/in/gbhopperiiiFollow Paul:LinkedIn: https://www.linkedin.com/in/thefpandaguyFollow Robert:Website: https://p3adaptive.com/Book: https://fairgamebook.ai/LinkedIn: https://www.linkedin.com/in/robcollie/In Today's Episode:[00:00] – Trailer[00:00] – How AI is changing jobs[02:43] – Robert's Microsoft journey[06:06] – Power BI and Power Pivot impact[11:25] – Leaving Microsoft for P3 Adaptive[15:43] – AI and the future of data work[19:33] – Making AI accessible[25:13] – AI tools and better workflows[31:11] – AI in career planning[33:38] – AI changing finance and consulting[35:16] – Why semantic models matter[38:35] – Building a strong company culture[40:34] – Robert's AI book and future plans

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 faster path to productivity.Learn more and submit questions: https://powerbi.tips/explicit-measures-power-bi-podcast/Episode event: https://www.meetup.com/chicagolandpowerbi/events/315711136/?eventOrigin=group_upcoming_eventsGet 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 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.Also in the news: Bringing Power BI Insights to Every Copilot User.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 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.Learn more about RayFin: https://www.microsoft.com/en-us/microsoft-fabric/features/rayfinGet 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/

Most companies are not short on data. They are short on the time, cost, and coordination required to turn it into action.Ethan Ding, co founder and CEO of TextQL, joins The Tech Trek to explain how AI agents are changing enterprise analytics. The conversation moves beyond faster dashboards into a larger shift, analysts managing fleets of agents, business teams asking far more questions, and companies finding revenue and cost opportunities that were previously too expensive to pursue.What Technical Teams Can Take From This• Making answers cheaper does not reduce analytics work. It increases the number of questions people ask.• Analysts may spend less time assembling dashboards and more time managing agents, data sources, permissions, quality, and costs.• The clearest ROI comes from decisions with direct financial outcomes, including fraud prevention, upsell opportunities, churn risk, and unused vendor spend.• Faster analysis matters most when teams can act on valuable opportunities they previously could not afford to investigate.• Token costs will force AI companies and buyers to reconsider where software budgets go, especially across BI tools and data platforms.Moments Worth Hearing00:00 Ethan explains how TextQL agents work across messy enterprise systems including Cognos, Teradata, Snowflake, Databricks, Tableau, and Power BI.04:52 Why giving people faster answers does not create free time. It creates even more demand for analytics07:10 How self service analytics quickly moves from asking what a number is to asking whether it matters and what to do next.10:08 The analyst role shifts toward managing fleets of agents and tuning an insight factory for the business.14:38 Why faster access to data can reveal valuable opportunities that were previously too expensive to investigate.19:55 A practical way to measure analytics ROI through fraud prevention, upsell opportunities, and other direct financial outcomes.24:18 How token costs, AI margins, and easier migrations could reshape spending on traditional BI tools.One Line That Stuck“It becomes much more of an operations manager job. It is a factory. It takes in tokens and churns out dashboards, reports, and recommendations.”Follow The Tech Trek on your podcast platform, subscribe for future episodes, and share this conversation with someone rethinking how their team works with data.

nFactorial Intelligence - еженедельный обзор новостей из мира стартапов и ИИ   Рекомендации от nFactorial  Ежегодный nFactorial Incubator Demo Day 2026. ​​24 июля, пятница, 13:00-17:00, г. Алматы. Вход свободный. Narxoz University, актовый зал, главный учебный корпус, Жандосова 55. Подать заявку: https://nfactorialschool.typeform.com/to/syWrSaRy 22-недельный буткамп по аналитике данных, 44 урока. 6 модулей: Google Sheets, Power BI, SQL, Python, Product Analytics, AI для Аналитика Данных - https://courses.nfactorial.school/da

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 show up in real Power BI environments — and what BI teams can do to become critical-thinking coaches, not just report builders.News this week:https://www.meetup.com/chicagolandpowerbi/events/315485409/?eventOrigin=attendee_listhttps://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Use-User-Data-Functions-to-securely-call-Fabric-REST-APIs/ba-p/5294590https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Streamlining-orchestration-with-smarter-pipelines-and-deeper/ba-p/5280154Get 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/

Healthcare organizations have more data than ever before, but turning that data into actionable insights remains one of the industry's biggest challenges. In this episode of The Beat AI in Healthcare Podcast, host Sandy Vance sits down with Nabil Jallouli, CEO and co-founder of Rollstack, to discuss how AI-powered reporting is helping healthcare organizations simplify value-based care reporting, improve decision-making, and scale personalized reporting without overwhelming their teams. Nabil shares why dashboards alone are no longer enough, why executives need trusted narratives instead of raw data, and how healthcare organizations can automate reporting while maintaining governance, security, and accuracy. Whether you work in healthcare leadership, data analytics, customer success, value-based care, or digital transformation, this conversation offers practical insights into using AI responsibly to improve reporting and business outcomes.  In this episode, they talk about: Why value-based care requires an entirely different approach to healthcare reporting The hidden "last mile" problem between business intelligence dashboards and executive decision-making Why healthcare organizations struggle with manual reporting despite major investments in analytics platforms How AI can automate repetitive reporting while keeping humans focused on strategy and relationships The importance of governance and trusted data in healthcare AI Why executives rarely spend more than a few seconds reviewing dashboards How personalized reporting improves payer, provider, and customer relationships The role of automation in scaling reporting across hundreds of healthcare partners Measuring ROI from AI reporting solutions and why reporting automation often delivers significant business value Why healthy skepticism around AI is actually helping healthcare adopt better long-term solutions How Rollstack protects sensitive healthcare data with enterprise-grade security and zero data retention policies What healthcare leaders should prioritize as AI adoption continues to accelerate A Little About Nabil: Nabil Jallouli is the co-founder and CEO of Rollstack, an enterprise platform helping companies like SoFi, Zillow, and Whirlpool automate their data-driven presentations and documents. Rollstack leverages deep integrations with leading business intelligence tools (Tableau, Power BI, Looker, and others) and AI to streamline reporting processes, including business reviews, EHR and HCP reporting, financial reporting, and client presentations. By eliminating manual copy-paste, reducing errors, and ensuring accuracy, Rollstack enables organizations to operate more efficiently and focus on decision-making rather than document preparation. The company is backed by Y Combinator and Insight Partners and is fully SOC 2 Type II and HIPAA compliant, meeting the highest standards of security and data protection for enterprise and healthcare customers. Before founding Rollstack, Nabil built his career leading data analytics and revenue strategy teams at Pinterest, Deel, and Groupon. Across these experiences, he observed a common problem: highly skilled professionals spending countless hours preparing slides and reports instead of focusing on high-value work and strategy. This recurring pain point ultimately inspired the creation of Rollstack. Nabil holds a Master of Engineering and dual Bachelor's degrees in Mathematics, Physics, and Computer Science from École Centrale Paris.

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 puzzle.From Purview's role to the risks of letting agents reason over permissions, they explore what it would take to make data governance in Fabric actually feel complete—and what builders like Taylor should ship now versus wait for.Mailbag question from Taylor B.: OneLake Architectural Guidance | Fabric Task Flow Studio | Chicagoland Power BI MeetupGet 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/

In this episode of The IT Experts Podcast, I hosted an MSP Insights Roundtable on AI, automation, and observability at scale, bringing together three brilliant guests, Joe Burns, Fiona Challis, and Nick Horner. What struck me straight away was how all three agreed on one thing before we even got into the detail. AI, automation, and observability only work when you understand your own processes first. Joe walked us through how his MSP, Reformed, built its operational maturity by identifying repetitive tasks, spotting where human error crept in, and asking his team what they actually disliked doing. Only once that groundwork was done did he bring in automation, including an early AI triage system on the service desk, and it paid off.    Nick added a perspective I loved, describing how starting small with clients avoids the scope creep that can derail an automation project before it even gets going. He shared a story about a modest HR automation that grew organically once the client saw the value for themselves, and how bringing end users into the process from day one builds the kind of trust that makes AI, automation, and observability actually stick. Getting genuine buy in, as Nick put it, turns a nervous stakeholder into a project sponsor rather than a blocker.    Fiona introduced an idea I keep coming back to, becoming your own customer zero, assessing your own readiness before you ever take an AI conversation to a client. She told us most MSPs score only two or three out of five on her readiness assessment, which shows how much foundational work is still undocumented across our sector. We spent time discussing how observability has changed, moving away from juggling dashboards across Microsoft 365, PSA, and RMM tools towards a single intelligent layer that pulls everything together securely and quickly. Nick made the point that speed and accuracy no longer need a dedicated Power BI specialist, and Fiona reminded us that the ROI conversation always starts with measuring a baseline before you change anything.    One of my favourite moments came from Joe, describing a law firm that spent three to four hours every week cross checking court lists against their case management system, a task his team solved with an agent in fifteen minutes. Fiona echoed this, encouraging MSPs to lead with one practical win rather than an overwhelming pitch, because solving a single small problem tends to open the door to many more conversations. We also got into the tension between compliance and outcome. Fiona argued that clients buy the outcome AI delivers rather than the technology itself, and Joe pushed back with honest feedback from his law firm clients, who want compliance answered first given how sensitive that sector is to reputational risk. Both agreed that governance needs to be built into the foundations of any deployment rather than bolted on afterwards.    Drawing on Daniel Priestley's thinking around demand and supply tension, Joe warned us against pouring all our energy into operational capacity while neglecting sales and marketing, a gap that can quietly erode margins even as efficiency improves. Fiona picked this up with real enthusiasm, describing how AI and automation can make selling feel far more natural, framing every client conversation as a business problem to solve rather than a service to pitch. She introduced the three pillars she coaches MSPs towards, capacity, experience, and revenue, and stressed the importance of owning your intellectual property rather than giving away your hard built agents for free.    We closed by sharing how each of us measures success, from outcome-based tracking to client and employee satisfaction scores, before final takeaways. Nick urged everyone to embrace the shift and stay ahead of the curve, Joe reminded us that capacity means nothing without the ability to sell it, and Fiona encouraged listeners to stop overthinking and take the first step. I came away from this session convinced, more than ever, that AI, automation, and observability can genuinely transform an MSP, provided the fundamentals are respected along the way.     Connect with Fiona Challis through LinkedIn and website.  Connect with Joe Burns through LinkedIn and website.  Connect with Nick Horner through LinkedIn.    Make sure to check out our Ultimate MSP Growth Guide, a free guide that walks you through a proven process to take your MSP from stuck to scalable, without working even more hours. It's 44 pages rammed with advice, insights and inspiration to help you decide what support is available to you now if you want to grow and scale your business. Click HERE to get your copy.    Connect on LinkedIn HERE with Ian and also with Stuart by clicking this LINK    And when you're ready to take the next step in growing your MSP, come and take the Scale with Confidence MSP Mastery Quiz. In just three minutes, you'll get a 360-degree scan of your MSP and identify the one or two tactics that could help you find more time, engage & align your people and generate more leads.    If you're serious about growth and want to explore what this could look like for your MSP, you can book a Right Fit Clarity Call with us HERE.  OR   To join our amazing Facebook Group of over 400 MSPs where we are helping you Scale Up with Confidence, then click HERE  Until next time, look after yourself and I'll catch up with you soon!   

QOTW: What does success look like on Excel and Power BI projects? Other nonsense:

Children's Nebraska transformed fragmented data into a strategic asset by creating a centralized data warehouse and executive-facing Power BI dashboards. In this episode, learn how the organization unified claims, financial, scheduling, and demographic data to deliver real-time insights, strengthen decision-making, and fuel growth across the enterprise.

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, SharePoint — and what a minimum viable harness actually looks like in practice.Inspired by this mailbag question: @HerrHippGet 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/

There's a certain type of person who first encounters Excel and, instead of running in terror, leans in and grins. Rob Collie has spent his career-from the Excel team at Microsoft to helping birth Power BI to now running P3 Adaptive—building things for exactly those people. He calls them "Crafters," and his new book, Fair Game: Customizing AI to Your Business Is Easier Than You Think, makes the case that this same crowd (hi, it's us) is uniquely positioned to do something genuinely remarkable with AI. Not because we're developers, not because we've cracked some secret, but because we've always lived on the boundary between the business and the tech-and that's precisely where the real AI work happens. The conversation covers the two "voids" crafters need to jump to go from chatting with Claude to actually building useful custom solutions, why the off-the-shelf AI tools are mostly useless for business purposes (and what to do about it), the faucets-first philosophy for semantic models, and why the developer isn't dead-just moving to the suburbs. Also: Tim built a quiz about his marriage and let his adult children take it. That happened. This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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 lay out a scalable architecture for ~9,000 users across 70 districts built around a centralized semantic model with incremental refresh.Resources mentioned: Chicagoland Power BI Meetup, Fabric Runtime Release Channels, Deep Dive into Tooltip Options in Power BI VisualsGet 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 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 move from experimentation to production.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/

Hay edificios donde la arquitectura marca el proyecto. Y luego están los centros de datos, donde son las instalaciones las que dictan las reglas del juego. Cuando un edificio debe garantizar funcionamiento ininterrumpido, redundancia, capacidad de crecimiento y consumos eléctricos descomunales, coordinar disciplinas deja de ser una cuestión de organización para convertirse en el propio núcleo del diseño. En este episodio hablamos de coordinación BIM en centros de datos, modelos federados, redundancia, estrategias de modelado, automatización de flujos de información y explotación de datos mediante Power BI. Analizamos cómo se diseñan infraestructuras donde cada decisión afecta a decenas de sistemas interconectados y donde el modelo BIM deja de ser únicamente una representación geométrica para convertirse en una herramienta de gestión. ¿Qué ocurre cuando las instalaciones dejan de adaptarse a la arquitectura y es la arquitectura la que debe adaptarse a ellas? ¿Cómo se coordina un proyecto que cambia constantemente sin perder el control de la información? ¿Puede un modelo BIM servir para algo más que detectar colisiones? Un episodio sobre infraestructuras críticas, coordinación multidisciplinar y una realidad que cada vez será más habitual: cuanto más complejo es un proyecto, más importante resulta gestionar correctamente la información que lo sostiene. Bienvenido al episodio 208 de BIMrras! Contenido del episodio: 00:00 Introducción al episodio y presentación del tema 02:10 ¿Qué es un centro de datos y por qué son críticos? 06:00 Presentación de Adrián Trujillo 09:20 Cómo llegó a la coordinación BIM de centros de datos 13:40 Arquitectura e instalaciones en centros de datos 19:30 Diseño basado en la demanda eléctrica (MW IT) 26:00 Cómo se diseña y dimensiona un centro de datos 31:20 Selección de la ubicación de un centro de datos 36:10 BIM, IFC y Power BI para explotar la información 44:30 Data Exchange y flujos de datos desde Revit 50:00 IFC frente a Revit para la gestión de información 55:20 Calidad de datos, familias y operación del activo 01:01:00 Inteligencia artificial y el futuro de los centros de datos 01:07:10 Fuentes de información, YouTube e IA para aprender 01:11:30 Despedida

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: https://community.fabric.microsoft.com/t5/Power-BI-Updates-Blog/AI-Powered-Power-BI-reporting-From-design-to-deployment-with/ba-p/5190703Mailbag from jedc: http://bi.foGet 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/

SQL is one of the most valuable technical skills for finance professionals, business intelligence analysts, and data analysts. But once you've mastered the basics, how do you write cleaner, more scalable queries that support real business decisions?In this episode of What's New at CFI, Meeyeon sits down with CFI instructor Joseph Yeates to discuss CFI's new Advanced SQL for Analysts course. They explore how advanced SQL helps analysts move beyond answering individual questions to building flexible, reusable data models that support reporting, dashboards, and business intelligence workflows.Whether you're working in Excel, Power BI, Python, or directly with SQL databases, this course is designed to help you collaborate more effectively with data engineering teams, organize complex SQL queries, and build stronger data analysis skills.

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 grinding the business to a halt.Also discussed: Replit's Microsoft partnership and Skills for Fabric in other harnesses.https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claudehttps://open-semantic-interchange.org/https://replit.com/partners/microsoftGet 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/

For years, Rob had a pretty good system. When a new technology showed up, he didn't immediately declare it the next big thing. He wanted to understand why it mattered first. Sometimes that meant jumping in early, like he did with Power BI. Other times, it meant waiting until the signal was stronger than the hype.   AI was different.   It was the first technology that made Rob question whether his usual approach was enough.   That's where Fair Game begins.   In this special episode, Rob shares the foreword from the audiobook, along with his introduction to Eddie, the AI collaborator that helped shape the book from first draft to finished manuscript. More importantly, he tells the story behind the story. How someone who never considered himself an AI evangelist ended up writing a book about it, why fear became an unexpectedly good teacher, and why he came away convinced that AI success has far less to do with the models themselves than most people think. If you've been hearing Rob talk about Fair Game over the past several months, this is your first chance to hear how it all comes together. It's not Chapter One. It's the reason there had to be a Chapter One.   Also in this episode: Fair Game Preorders

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 scaling AI-assisted analytics.Read more: https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claudeGet 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/

Lynn Gravley, the newly appointed chairman of the Transportation Intermediaries Association (TIA) and founder of NT Logistics, joins us to break down the real side of the freight industry! Lynn shares his journey from being a broke, freshly minted college graduate to building a thriving managed transportation business. He dives into how managing full networks differs from traditional freight brokerage, the massive role of data analytics and Power BI dashboards, and why aligning with the TIA is a game-changer for building authority. If you are ready to stop fighting fires and start optimizing your logistics network, tune in now!   Connect with Lynn Website: https://www.ntlogistics.com/ / https://www.tianet.org/  LinkedIn: https://www.linkedin.com/in/lynn-gravley/  

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.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/

In today's Cloud Wars Minute, I break down how DynaTech Systems enabled Solmax to turn operational complexity into global efficiency with D365, Power BI, and Microsoft Fabric. Highlights 00:03 — Today I want to take a bit of a dive into a specific case study: the story about the impact of digital transformation enabled by one company on the business outcomes of another. I love having the opportunity to explore stories like this because, as important as it is to discuss the technology itself, how it's implemented and what that implementation can lead to is just as critical. 00:41 — Solmax is a leading geosynthetics manufacturer focused on civil and environmental infrastructure, operating across four continents through 32 legal entities. This broad reach, although great from a growth perspective, was creating challenges such as data silos, inconsistent processes, and a lack of standardized reporting, which affected financial and operational insights. 01:08 — Beyond this, manual processes led to inefficiencies. Complex sales price calculations hindered productivity, and reliance on outdated Microsoft systems resulted in slower Power BI report refresh times. To address these challenges, Solmax had a core goal: the One Organization, One Data, One Reporting initiative. 01:52 — DynaTech has a number of solutions it will tailor to suit the outcomes of an individual client. In the case of Solmax, the company opted for its finance optimization solution. After process consulting, DynaTech enabled a greenfield implementation of D365 Finance and Supply Chain Management with unified processes across 32 entities. 03:17 — Beyond this, unified real-time dashboards enhanced global reporting, supported faster decision-making, and improved the company's audit readiness. Solmax was able to reduce freight costs, accelerate delivery cycles, improve truck utilization, minimize penalties, and shorten accounts payable and receivable processing times. Less manual intervention meant fewer errors. Visit Cloud Wars for more.

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: https://claude.com/blog/how-anthropic-enables-self-service-data-analytics-with-claudeGet 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 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 practical first steps a Fabric team should take before turning it loose in their tenant.https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Introducing-Rayfin-A-new-AI-first-way-to-build-deploy-and-govern/ba-p/5191676https://azure.microsoft.com/en-us/blog/microsoft-build-2026-building-agentic-apps-with-microsoft-fabric-and-microsoft-databases/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 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 touches production data.https://azure.microsoft.com/en-us/blog/microsoft-build-2026-building-agentic-apps-with-microsoft-fabric-and-microsoft-databases/https://community.fabric.microsoft.com/t5/Fabric-Updates-Blog/Orchestration-in-Fabric-Data-Factory-Build-2026-recap/ba-p/5185775Get 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 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.https://github.com/microsoft/fabric-task-flowshttps://learn.microsoft.com/en-us/fabric/cicd/deployment-pipelines/get-started-with-deployment-pipelines?tabs=from-fabric%2Cnew-uihttps://learn.microsoft.com/en-us/fabric/cicd/variable-library/get-started-variable-libraries?tabs=home-pagehttps://github.com/mattpocock/skills/blob/main/skills/productivity/handoff/SKILL.mdGet 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/

We've informally heard that Satya is a listener to LS for a couple years now, but it was still absolutely surreal to meet him and do a live pod at Build, together with our friends at No Priors, the leading VC AI Podcast that we also greatly admire!We covered the MAI model technical takeaways on yesterday's AINews, so I will focus our recap of Satya's main messages around three elements:* Satya's adaptation of the Bill Gates Line for positioning Microsoft as the Frontier Intelligence Platform — customers must gain much more value from the Microsoft ecosystem than Microsoft itself, by building on multi-model harnesses like OpenClaw and Scout, drawing on the full enterprise context exposed by context layers like Work IQ (heavily dogfooded by his C-suite), and building up private evals and traces as a new form of Token IP* AI ROI: On one hand, enterprises are having difficult conversations around Tokenmaxxing and Layoffs, and on the other hand, there are serious re-evaluations of the End of SaaS since the Build vs Buy equation has changed so much. Our previous SemiAnalysis guest had… interesting comments on Microsoft's position on this as the ur-SaaS titan, and Satya had great answers* Making the Impossible Possible: Kevin Scott's inspiring framing around what the most ambitious version of applying AI and technology at large to business and social problems, like education and social impact.Enjoy!Full VideoTranscriptVoiceover: Welcome swyx, Sarah Guo, Elad Gil,, and Chairman and Chief Executive Officer of Microsoft, Satya NadellaSarah Guo: Welcome to a crossover episode of No Priors and Lane Space with Satya Nadella. Um, congratulations on an amazing build. No, thank you so much, and it's great to be with both of you. I listen to both of you or b- both the podcasts all the time. It's great to be on it.Thank you so much. [00:01:00] So you're just talking about, um, these amazing, uh, announcements from across the Microsoft estate all morning for, I think, three hours. What is the, uh, what's the most important reflection or takeaway you have?AI as an Ecosystem PlatformSarah Guo: I, I'd say there are, uh, perhaps the, the biggest one for me is let's sort of conceptualize this more as an ecosystem play as opposed to a single model or even a single platform, right?Satya Nadella: I mean, you know, whatever I... At least for me, having grown up at Microsoft, having seen, whatever, four major platform shifts, uh, I sort of fall into that, um, uh, camp where a platform is defined by fundamentally its ability to create more value about the platform versus what's captured in the platform. And so if you, you view what's happening right now, I think this morning's keynote was how can any company, whether it's an AI native company or a traditional enterprise company, participate as a first-class participant where they can point to AI they created, [00:02:00] right?It's not that they don't use other people's AI. Of course they will. But to me, what's the path? What's the recipe? How do I do it? What does a stack look like? What does the tooling look like? What is valuable? How do you do that? That's it. That's sort of our job to do. Yeah. Ecosystem strategy is, uh, very complicated, right?Sarah Guo: Because you end up building certain components, partnering for certain components, supporting them. You just announced this big suite of models. Like, tell us a little bit about the, uh, training strategy for Microsoft now. Yeah.MAI Models & Training StrategySarah Guo: So, so the thing that we wanted to do with the MAI models was to build, and as Mustafa talked about, first of all, a great lineage, right?Satya Nadella: Starting with pre-training, uh, with very good data quality, uh, doing all the ablations, making sure because in, in some sense it's becoming even harder to build a clean lineage model just because there's so much stuff out there, uh, that you truly need to ablate out to be able to have a fantastic [00:03:00] pre-trained model.In fact, that's one of the challenges of a lot of the open weight models is they look great on one benchmark or two, but they're not great on practice. So that's why, in fact, even in the RFDEs are, they, they are pretty gone really excited about these MAI models because how the heck can a small five B model hill climb?Uh, and it goes back a little bit to what I think is ultimately the key thing to do, which is try to pursue finding that cognitive core. Uh, so to me, starting with a clean lineage- Then creating that ability for companies to be able to use this, right? Not just as a generalist, but to create their own specialist by building this hill climbing scaffold around it, right?So it's not just the model, but you have a hill climb scaffold around it, then you will start building your RLE. You will start collecting the traces. Most importantly, you'll have private evals because we know all the evals out there are good, interesting, [00:04:00] but they're not really that critical- They're work, yeahSwyx: at this point because they all can be maxed. And so the point is each company will have its own private eval. And so that end-to-end platform story around our models is sort of, uh, what I think is interesting. And then the one other thing, Sarah, since you brought that up, is I do feel there's a new frontier.Satya Nadella: Like people talk about the frontier and are you operating at the frontier. Um, interestingly enough, if you add a little temporality to it, you can use, let's say, in, in, in fact, the, the Lando Lakes demo we showed was pretty cool. We used, whatever, GPT-55, right? Then you collected a bunch of traces, and then you took a 5B reasoning model and achieved higher.Sarah Guo: Uh, so that is another aspect of what it means to appear... uh, you know, operate at the frontier Yeah. I, I think, uh, I first of all have to congratulate you on basically building a frontier neo lab inside of Microsoft in two years. Um, I'm wondering, you know, you have all this AI strategy that you're rolling out.Lessons from Two Years of AI DevelopmentSwyx: I'm wondering, what do you know now that you wish you would tell yourself two years ago where- or two or [00:05:00] three years ago? Three years for the Jensen partnership, two years for, uh, MEI. Yeah, I mean, I think the, the thing when, that I reflect quite a bit, right, which is sort of obviously I got into all this when I got excited by the, the scaling laws paper and, you know, when, you know, even the OpenAI partnership came about when those folks said, “Hey, we're gonna really throw a lot of computer transformers.”Satya Nadella: Uh, and they've helped. I- the thing that I always look back and say, “Wow, these things, uh, do have capability that they're climbing up.” W- I mean, this, you know, this crude way of saying it is intelligence is log of compute kind of works. Now what I think we underestimated perhaps is the real-world complexity of deploying these so that they actually deliver the value in the real world, right?So the outcomes as measured by any benchmark is interestingly important, but the true eval is when people out there are able to do unique things that they only can value, and it's very [00:06:00] measurable, right? That I wish we had sort of even, like, had more in our consciousness, right? Which is as an industry.Sarah Guo: Because right now I think when people say, “Wow, I don't want a token max,” it's an artifact of us not having thought ourselves as an industry that we are using tokens to create value every step of the way. So I think that's kind of what I wish we had gotten there, but I'm glad we are here.Real-World Value & Use CasesSarah Guo: What are some of the use cases that you've seen that have created the most value for your customers?Because I know that people talk a lot about code, and I think it's pretty clear that that's something that's having very large scale impact. Are there other areas that you find in common that your customers are really benefiting from? Yeah. I think, yeah, to your point, obviously coding is now got... But it's interesting, by the way, Elijah, to even talk about the coding, right?Satya Nadella: Which is coding has worked so well that we now have to rebuild the IDE, right? I mean, it's kind of nuts to see what we sh- launched is like, oh my God, I have these hundred agent sessions. I... The cognitive load it transfers back to me as a human is so [00:07:00] excessive that now I need a new UI. Uh, oh, by the way, I, like the, the chat as the only artifact was also impossible, so that's why we need a canvas.So it's kind of interesting for all the things about where is software needed or where is UI needed, uh, you kind of need that even for code, right? In a fully agentic world. But that said, one of the things that we are starting to see, we started seeing with co-work, but even some of the work we, we showed with auto com- uh, um, autopilot Right on what you see with claws is a good one because if you sort of think about a lot of human capital is doing the glue work, right?If you now can augment that with tokens/agents that are long-running, durable, right, then your ability to scale even what is still judgment and glue work gets amplified like coding does. Uh, so you can... Like, I'm positive that six months from now we'll all be saying, “Oh, wow,” like, all through ni- the night there was a bunch of stuff that [00:08:00] all these autopilots that I have working on my behalf with my delegated authority, so to speak, right?I can... Sort of given even my identity, did a bunch of work, then of course I'll need my new ADE to say, “Well, what did you do?” Like, I might... “Did I do this work?” And so on. So I think that that's where compressing of workflows, uh, completing of tasks, uh, that's where I think a lot of the value gets created. I think you raised a really interesting point, which is there's the actual agent that's doing the code, and then there's a harness around it, and that's the environment, that's the context, that's everything you're setting up as a developer around actually a coding agent.The Harness Concept for Enterprise AISarah Guo: What is the harness for the enterprise? Is there an equivalent concept for broader productivity work, or how do you think about that concept sort of generalized? That's right. So, so in some sense you kind of want the harness to define the models, the, the data, uh, and the tools, and so that you have a loop across those three.Satya Nadella: And so what we are trying to, first of all, make sure is each of our products that we build, right, whether it's GitHub Copilot or the security copi- the, the [00:09:00] stuff we showed with MDASH or even the discovery for science, it doesn't matter, all of them are multi-model harnesses, um, with tools access so that you can do this progressive, uh, disclosure of tools even so that they're token efficient.Uh, and then you're feeding it with very rich context because that's sort of the other hard lesson we have learned in the last two years is, oh my God, the amount of work you need to do to prep the context layer, uh, such that your plan can execute in the most efficient way is where the magic is. So we have, in our case, we have the GitHub harness, which essentially we're using across all our products.It's available in Foundry, and we are open, like you can use your Llama harness, whatever. Or you can use the, um, uh, you know, any open harness or any harness of yours and train with your tools and multiple models and your context. And so that's the pitch. Because right now a lot of dialogue is, um, “Hey, if I train the harness plus tools and the model together, you get [00:10:00] evals.”Elad Gil: And what we are proving out is... And the best example of that is what we did with MDASH, right? Because when it launched, uh, it found bugs or vulnerabilities that were not found by Mythos Uh, and so there is existence proof, I would claim, that you can have a multimodal harness, uh, that can in fact be more, uh, performant in the real world So a premise behind the, uh, training at the independent frontier labs is really, you know, we're gonna have these models, and we'll have an API business, and we'll support enterprises and startups.Sarah Guo: ButPlatform Strategy & Developer EcosystemSarah Guo: a first-party product, be it productivity or code or search, drives the majority of revenue. That's a different value equation than you're describing, I think, with the Microsoft ecosystem. Uh, if, if that's the case, tell me if it's the case, uh, ‘cause obviously you have first-party products and you have enablement products.Satya Nadella: Um, what is the role of the develop- Like what is gonna be hard and the set of skills and the value capture the developer has in that world? Yeah. So I think that there's always [00:11:00] gonna be the case that someone who is super successful in- as a platform builder can also have first-party products. It was true with Windows.It is true, uh, with, uh, the, the SaaS side and the cloud side as well with us and others and so on. But the thing that is, is it should not be a limiter to other people achieving that same success, right? That I think is the core difference, which is the, the network effects this time around, around intelligence are such because they learn from data, and not really lots of data.It's just a few samples that you have to see to understand what's novel about something. So that's why the game becomes how to protect. So that's why I would say every company, having private evals may be the biggest IP, right? Think about it, like what's that private eval that you can then use even a frontier model to hill climb on and not leak the traces may be one of the biggest [00:12:00] drivers, uh, of IP.Like, so in other words, another te- acid test is you have an eval that's private. You're using, uh, a g- a Model A. Can you switch it to Model B and e- you know, climb up? If you can, then you're in control. If you can't, you're not in control, and that's where even the harness decision becomes super important, right?swyx So therefore, having an open harness, letting all models come in, having your evals, your context, your tools help you hill climb, I think is the skills that an AI native startup needs, a SaaS company needs, or every enterprise needs. Yeah, I think in, in a very real way you are ... Microsoft historically is an operating systems company and th- then become a cloud company.Maybe like the third act is that you're a harness or evals company. Whatever w- ... whatever the, the sort of conglomerate of concepts that you wanna put together. Um, and, and I think like enabling every company to have like frontier intelligence or what- what- Yeah ... I forget the, the [00:13:00] exact term that you used, um, is the, is the mission, right?Satya Nadella: That's it. Like that is, that is the platform promise, that you build with us, you will get your intelligence, uh, for your data. That's it. That ... To, to me, that is the ... Like if there was one tagline, uh, for this entire developer conference is- Can everybody operate at the frontier with their frontier intelligence, right?To me, that is so important because otherwise it, I, I don't know how you achieve stable equilibrium, right? Which is how do I then go and say, “Well, my company is gonna have a terminal value because I now know how to continuously compound-” Yeah ... on top of what's a platform that gets better,” right? So when, like Windows obviously came out, Adobe built, Autodesk built, uh, or even like take what Jensen said.We built DX and he built, you know, CUDA on top of it. Um, right? I mean, I always say to Jensen, “God, I got the short end of that,” right? “I wish, uh, we had recognized it.” But nevertheless, but that, that idea that you can build a platform layer [00:14:00] that someone else can then extend out, um, and build their own intelligence layer in this case, I think is everything, right?Without it, why have a developer conference? I can just come and have you all sort of just worship at the altar of one model. Yeah. But that's not a developer conference. Uh,IP, Evals & Company Valueswyx: backstage we, we had a discussion about what is IP or what is the, the value in a company. It used to be the length of, uh, human experience at a company, and now it's this other thing which is the evals, the, uh, experience in sort of applying agents to the company. Can you... I just want you to like flesh that out a bit more ‘cause- Yeah ... it was very insightful.Satya Nadella: It's a great way to frame it, right? Because yeah, at the end of the day, every company is gonna have both the human capital that is still gonna be super valuable, uh, because humans, uh, and their ability to find the gaps that exist at all times is going to be the way we all will create value, right?I mean, so I'm definitely in the camp that this is going to be about expressing new forms of human agency and ambition even as token capital goes up, right? So let's say a cor- any corporation [00:15:00] has lots of tokens and lot of human capital. The question is how do you compound the two? So if you have a... Like if you take in Teams I have a bunch of agents doing work and a bunch of humans doing work, and the traces between those, that is really important context of how that enterprise is creating value.Then that goes back to train not a generalist model, but to train the company veteran agent, uh, right? That is super valuable again, right? Which is when a company goes says, “It should in fact go onto the balance sheet,” is how I think about it, right? That's so... In fact, there may be... Like human capital was never possible to go put on a balance sheet, uh, because you didn't know how to capture the tacit knowledge.swyx: Whereas now I think you can with the agents that have learned through the h- through, through time, through all the traces. Uh, so that's what at least we think will happen. I, I think the SEC is gonna have to have accounting standards- ... for token, uh, expertise Uh, y- y- you're talking about the equilibrium [00:16:00] state, um, and a stable equilibrium where companies have this compounding value and can see terminal value for themselves.Future of SaaS & Business ModelsSarah Guo: Another challenge to, you know, the considered equilibrium of, okay, there are applications and workflows that are sort of common to a vertical or a horizontal. Um, and this was, like, the generation of SaaS companies and, you know, Microsoft has lots of SaaS properties as well. And then there are things that are very specific to every enterprise that they're differentiated against.Elad Gil: Um, I'm sure you have heard much and participate in much of the debate about the end of software because all these workflows are, are cheap to generate now. Um, do you think the equilibrium looks different between what agents get built- Yeah ... in enterprises versus in their vendors in the future? Yeah. So I think what's happening there is, see, we, we had a particular way we captured, um, I would say workflow in apps, right?Satya Nadella: Because we built a, a data model, right? We schematized some part of some business process. Mm-hmm. We then built a bunch of business logic. Yep. And then we put a bunch of UI [00:17:00] on top of it, right? So that's kind of what every SaaS company- And a little configuration. For, like, 20, 20 years that was the plan.Right, that- Yeah ... and that was it. So interestingly enough, now you kind of get to re-litigate that vertical stacking, right? So I still think, for example, that data model that you built underneath every SaaS application is super good, right? Like, why reinvent it? Like, I, I, my general ledger better be a general ledger.I don't need new schema creation. No. Uh, in fact, that entity relationship, uh, is actually pretty good, robust thing that I want to feed. And you want it to be stable. That's right. Yeah. Then same thing with business logic, right? If, if you look at, uh... We have this product called Power BI, right? It is like dashboards galore people created.The beauty underneath that dashboard is a very rich semantic model, right? Someone took the pain to create a dashboard and do all the measures, and you want that. That's business logic, right? I want that to be available to me. So I think the [00:18:00] challenge of the SaaS business model is we packaged one way. We now have to learn how to unbundle these things and rebundle in new ways and discover new business models, right?I mean, if you look at it, d- what's happening today with Microsoft 365 is a great example, right? We have this thing called Work IQ. In fact, like, what we are realizing is, oh my God, like, you know, if you look at... In fact, there's a pa- historical parallel too, right? We sold first Exchange and SharePoint and, uh, you know, before Teams, we had a thing called Lync Server and what have you, and we thought, “Oh, that's all gonna move to the cloud.”But little did we realize that, um, the number of people who will use servers in the cloud is 10X, 100X, right? Because people were not buying servers, they were just buying a subscription. Mm-hmm. The same thing is now happening with M365 because with Work IQ, we have exposed what is perhaps the most important database in a company that never got used as a database because it was only captive to our apps.Mm-hmm. Right? It, it was all email operated on it, Teams operated [00:19:00] on it, Word, Excel, PowerPoint, SharePoint. But now, like this is one of the coo- coolest things I get to do with Work IQ. I go to a GitHub repo and I say, “Hey, I attended a bunch of design meetings last week related to this repo. Can you capture all that and tell me what changes I should make?”I mean, think about that, right? It literally can go look at all those transcripts, come back with a plan to change a code base, right? Previously, you could never have thought of using M365 for something like that. So the value creation opportunity now in the agent world is in fact 10X more, but it does require us to have...Sarah Guo: For example, there's going to be usage around M365, right? Which is going to be perhaps more than even the e- end users and we have to even re-architect. Like, in fact, like what I use to serve an inbox or a mailbox cannot be used to serve an agent. Uh, and so that's sort of what we are doing.Pricing Models: Per-User, Consumption & OutcomesSarah Guo: I don't believe in, like, permanent business models for any of these domains, but in the [00:20:00] near term, do you have a prediction between, uh, you know, outcomes-based pricing, token-based pricing?Elad Gil: Enterprise bundles Yeah. The way I- I think about this is always we've had... Like, let's even take the per-user pricing. Mm-hmm. The per-user pricing is really an artifact of someone creating a budget needing certainty, right? Because it's the most important thing. Like, somebody wants a budget- Mm-hmm ... they need a per user.Satya Nadella: And, and per user is just a set of entitlements to usage, right? That's kind of what it is. And so the way is, if the first bundling will be take some usage, bundle it into per user stacks and, you know, then sell subscriptions. So subscriptions I think are gonna be there, per user is gonna be there. Then the next big thing will be consumption.So people will say, “I want consumption.” And it's also possible that people will say, “I don't even want to pay for any of the subscriptions or the consumption's outcome.” Mm. But remember, most people love outcomes until they have an outcome, because once you have an outcome, it's like giving away royalty, [00:21:00] right?Mm. I mean, like I, I've talked to customers who love, you know, outcome-based pricing, and I say, “I'm all in,” until they, “Oh my God,” like, “what are you talking about? You're sharing in my outcome? No, no, no. I want you to go back to per-user pricing, and I want you to consumption price,” right? So I think that debate will go on.Uh, but and all, all, all of these business models have a particular time and a place versus one to rule them all. And if anything, if you're a SaaS vendor or you're a platform vendor, having that flexibility... And quite frankly, we face this with GitHub, right? We just recently announced a per-user pricing on GitHub because little, you know, we- GitHub Copilot was constructed at a per-user level before we understood even, uh, the intensity of usage of agents, right?It was an interactive way for a developer to use code complete, maybe tasks. It was not like, oh, I launched 10,000, you know, agents that are going on all day, right? So that is what the adjustment is about. So now that we really want, there will [00:22:00] always be a per user, but there will have to be a consumption meter.Durability of SaaS & Build vs BuySarah Guo: How do you think about the durability of SaaS more generally? One thing I've observed is in a lot of enterprises internally, there will be teams that almost have agent euphoria. They're so excited about the explosion of things they can build that they're trying to rebuild a lot of applications or going to their SaaS vendors and saying, “We're not gonna work with you anymore,” or, “We're considering an internal project.”And it seems like in six to nine months, maybe some of those people will come back and say, “Actually, we, we can't rebuild everything.” How do you think about what's durable in this world and what isn't? Yeah, it's a... It... I think we have to go through one full budget cycle on this to really see the, um- Uh, the sort of the emergence of the equilibrium, because at the end of the day, there's marginal cost to even generating the app, right?Elad Gil: In, in fact, there can be even a, a simple way to say it, like if you should always acquire something if the marginal cost of building and maintaining, uh, something on your own is higher. Uh, right? That should be like it's a quantifiable- Yeah. Right? A quantifiable thing. And [00:23:00] the maintenance part is important, right?Even, like you got to remember like, hey, you know, all the security stuff that now AI will find, you better fix them too fast. Uh, of course, there's a coding agent to help you with, but then that burns tokens, right? So whose responsibility is it? It's kind of like a, a cycle that you've got to think through.And I think we have gone through the excitement that I can generate a lot of software. I think the next thing would be what software do I really want to generate? Mm-hmm. What software do I want to use from others? How do I compose these two into some agentic workflow that I have agency over, right?Sarah Guo: Because I think there'll be very little tolerance for anybody who's inflexible, uh, at the vendor level. Uh, but at the same time, I think that anyone who has got that flexibility shows up, delivers the value, will be back at again, right? We're selling software, uh, but with just different business models, in fact Uh, speaking about building software, um, one of my favorite moments from, I think, a previous build maybe one or two years ago was they had a b- they, they...Swyx: There was a section of you building your [00:24:00] own software. I'm curious if you're building anything now. Yeah. So I, I think the... You know, first of all, let's face it, right? Building software has made it possible for even the incompetence of a CEO of a company- ... like ours, uh, you can build, so thank God. But that said, I, I, I, I do feel that, you know, something like, um, GitHub Copilot to me, and especially the new Sessions app or the new app, has just made it so much more possible for you to have agency over artifacts that you felt you couldn't touch before, right?Satya Nadella: So to, for me as a CEO, even to go to a code base, uh, to be able to learn about it, like I remember joining Microsoft long back, you know, first and then you say, man, everybody had to go in and look at, you know, whatever, Cutler's, Malik, or what have you to learn how to do good C, uh, C++ code. Um, so now that ability to be more full stack up and down is so good, but that doesn't mean every one of us should be doing the same thing.The question is: [00:25:00] how do you then have the ability to inspect things, learn things, see things, um, I think is just so much more. And so to me, what I'm building a lot of is these long-running Foundry agents. Uh, right? So there's autopilots. So the easiest thing is, to me, I think I just built one, uh, even last week, where the idea was, hey, can I have an agent that is continuously monitoring essentially my own chief of staff autopilot, right?We're gonna have that obviously in, uh, Scout. That's what, uh, uh, we showed. But it is so easy and trivial to build. I took Work IQ. I said, “Take Work IQ, go, uh, and build a Foundry long-running agent.” Uh, store all the memory in, um, uh, using Ray Fin, right? Basically at my backend as a service. And lo and behold, it built it, and not only built it, I could say publish to Teams, and it published the damn thing to Teams.Sarah Guo: So the ability, uh, to have a, you know, some end-to-end project like this complete is just pretty [00:26:00] miraculous. How do you think, uh,Future Engineering RolesSarah Guo: that impacts the different types of engineering roles that exist in the future? Because right now I think there's, you know, a dozen different types of engineers that you can be, from QA, front end, et cetera.You know, there's a big swath. I've heard some people argue that in four or five years we'll basically end up with four engineering roles. It'll be people who are managing agents, it'll be four deployed engineers or FDEs, it'll be security engineers, and then people working on large scale infrastructure for a small number of services, and then everything else just collapses into the agentic world.Satya Nadella: Yeah, I- Do you think that's a correct view of the world? Yeah, I mean, I think, I think we'll have to experiment our way through it. But what you said is what... There are some very at scale things. At LinkedIn, they did structurally change- Mm-hmm ... uh, and it, you know, basically built up a new discipline called full stack builder, right?So they went and said, “Hey, let's bring, uh, people from design and product management, front end engineering, all put them together.” Uh, but also have an edge, right? It's not like the design person still doesn't have the design edge, or the front end [00:27:00] person doesn't have the front end edge, but you can give yourself bigger scope in roles so that you're not confined to one role.Um, and then r- equally, infrastructure has become very critical, right? So in other words, like, I mean, RLEs, I mean, one thing we've realized is even for the Excel team, for example. Mm-hmm. Building the RLE in which a reward can be learned is actually one of the hardest sort of infrastructure problems.Mm-hmm. Uh, and so you kind of need even new talent, right? Distributed systems people even in what was considered an end user app team, uh, because it's a different skill set. So yes, infrastructure, science is the other one, obviously. Um, so I think we'll see how these evolve, right? Where's the s- real... I mean, always the world will have a bunch of specialists.Okay. Um, you know, I think the generalist role is going to be the most exciting, right? Because the leverage of a generalist- Mm-hmm ... um, is where we are going to see the maximum returns, right? When, when you said, “Hey, are you coding?” I'm now a gen- Like, what... I've basically translated [00:28:00] knowledge work Right?Which I did, where I created a Word document or a spreadsheet, or even, uh... And now I can build an app, right? It's in the same sentence. Uh, right? That idea that, “Oh, wow, my generalist skills have gotten higher leverage,” I think is what we're gonna see across the board. Music to the ears of CEOs and VCs that are, like, a little dangerous and a lot of- Golden age for idea peopleSarah Guo: idea people. Yeah. Uh- With a lot of agency. I- if you take that idea of personal agency and you just zoom it out to the organizational context, um, uh, my partner Mike Renall, who, uh, actually started his career at Microsoft, just wrote an essay where one of the big takeaways is i- it's an age where you can be much more ambitious, and you need to be, given the pace of the environment and how quickly, actually, users and companies are open to adopting new technologies.Satya Nadella: Um, how do you think about... I, I feel silly asking this of somebody running a, you know, trillion-dollar-plus company already, butAmbition & Making the Impossible PossibleSatya Nadella: how do you think about how Microsoft can be more ambitious now? It's a great question. Um, I [00:29:00] think, um- I think the, the thing in these type of transitions is to have a conceptual model of how work can change to go after outcomes that you could hardly imagine previously, right?In fact, Kevin Scott has this nice line, right, which is, um, when you can make the impossible... Like, when you're making hard things easier, that's sort of one point of leverage. But true ambition is about making the impossible possible. So now the thing that is missing a little bit in all of our organizations is what is that new conceptual model of what can we build?What was impossible and what can we build? And I'll give you one example of this, right, which is I take great inspiration from sort of the people who were managing the Azure net- network. And they came to the... This was from even last year. You know, we were scaling. You saw that I, I [00:30:00] talked about sort of how we built in the last 15 months more Azure capacity than we built in the first 15 years.I mean, it's crazy. Wild. Yeah. Right? It's pretty wild. And it's the same team. So they saw that and they said, “Bob, this just ain't gonna work if we don't reconceptualize our work.” So they built... Essentially they said, “Our job is not to do Azure networking. Our job is to build the agentic system does, that, that does Azure networking,” right?These are the folks managing the 500-plus fiber operators managing the VAN, right, all over. And fiber operations ultimately is a physical operation. Things get cut, things get, uh, you know, have to be repaired. You know, we have fancy words called DevOps and so on. Basically, emails are coming in and you gotta go respond to them, take care of it.So they built this agentic system. They even have a character for it. It's called Miles, and it sort of does all this stuff, right? They started sort of screaming for more tokens and so on. And so they were saying, “Look, uh, we don't need a headcount. We need tokens in order to be able to [00:31:00] manage, uh, our operation.”That reconceptualization- Mm-hmm ... of what their work is, right? They, they basically took their work and made it meta, right? That meta work is now their new work. Mm-hmm. Right? In the ‘80s, if somebody had come to us and said, “4 billion people are gonna get up in the morning and start typing,” my model would've been, we need 4 billion typists?But we're not doing typing, we're doing knowledge work. So that, to me, I think is it, right, which is whether it's Microsoft or whether it's any organization, is to give ourselves permission to do new types of metacognition, meta work, using these new tools to change the outputs that matter, uh, and then really make the impossible possible.Sarah Guo: So completing that dot or the, the connective tissue across those, I think, is where a lot of the enterprise value will get created.Data Center Build-Out & Community ImpactSarah Guo: Should we talk about data centers? Yeah, please ask. Oh, okay. Well, uh, uh, w- we-- this leads nicely into the data center build-up. I always think, I- I just-- I'm just impressed at the sheer scale of the [00:32:00] build-out from Microsoft, but also everyone else, that this is redefining what it means to be a hyperscaler.And I just feel like that, that, that is at unprecedented scale on finances, uh, on the way you run the company, but also the communities that are, that are impacted. Um, yeah, just talk a bit more about what you're seeing on the ground, like when you visit your- Yeah, I think there are two aspects of it.Satya Nadella: Obviously, the, the build-out is, uh, extraordinary. Um, you know, nothing like this has happened, and it's great to be, uh, one of the participants in it. Uh, but you brought up the other part, right? I think at this point it's clear that unless we as an industry, uh, are very principled about ensuring that the benefits of all the stuff we're talking about are felt in real ways, uh, at the community level, right?Because this is not just a, a campaign, um, right? It has to be real, where people are saying, “Look, this is not ch- changing the prices on energy for me.” In fact, if anything, it's bringing down prices because long term there's going to be a better [00:33:00] grid, there is going to be more energy. Water consumption is, in fact, not sort of, uh...In fact, water is being replenished, right? You gotta really, you know, educate folks on truly what's happening, the cl- uh, the closed loop systems we are building. We have to invest in the training, the jobs, the tax base. In fact, the least talked about stuff is the amount of jobs that get created during construction, after construction.What's the tax base that's there in the community? And, and all this has to be real. Um, and, and if that is the case, then we will have permission. If it is not, we won't have permission. It's as simple as that, right? Which is, uh, we, we... I think we have to take it as an industry pretty seriously. Uh, I think it's good for communities to be skeptical, ask the hard questions, for us to do the hard work, earn that.Um, but at the end of the day, if there's-- if we can really be the produ-- Wait. I've always felt like in human history, if you use a lot of energy but also create a lot of value for society- The story has been fantastic. If you don't [00:34:00] do that, it's not been that great. And this time around, I'm a firm believer that ultimately if you do have a token economy that drives productivity, that drives economic growth, that drives broad spread, um, you know, participation, better health outcomes, um, then I think we'll be in a great place.Sarah Guo: Uh, and that's at least what we all have to be focused on. Yeah. It, it makes me think actually that with all these initiatives that you're doing, might be e- easier to see ROI in the communities first before in enterprise. Yeah. I, I mean, I think both sides. Yeah. In fact, it comes back together. It has to be the people in the communities are going to be employed, are going to be participants, uh, in the real economy, right?Satya Nadella: That's I think the question is. Like, if we- if the broad economy is doing well and the communities are doing well, the dots get connected. It's sort of the market forces are such that we will connect the dots. And that I think is it. Like, you ought to be able to see the evidence. You can't be about o- any one company, uh, but it has to be broad economic growth and broad [00:35:00] ec- you know, community permission.Elad Gil: Yeah. I guess I wanna talk aboutSocietal Impact & Optimism About AIElad Gil: what you're most optimistic about currently or what have you most updated your personal models on regarding societal impact of AI? So you're saying what's the, the, the- What have you updated most on in terms of societal impact of AI? Yeah. I think the, um, the p- the most, um- Critical thing is the first question we even started with, which is we need to tell the story and make it real that everybody has a real shot to participate as a first-class participant in this new economy.Satya Nadella: Right? That's kind of, I think we- in the next 12 months, 18 months, we need a way for people to say, “Oh, wow, I get it.” Right? There's going to be tremendous capability, tremendous amount of infrastructure, but I can see what is going to happen, whether it's the benefits like health outcomes or my ability to create a startup or my ability to run my [00:36:00] local sort of, uh, store more efficiently.It's just happening, and I see that, uh, benefit myself, right? That to me, you know, earning that permission in a path-dependent way, we can't wait. See, the one thing, Eli, that I've now learned is I think the world is gonna be very skeptical of tech and tech companies that say, “Trust us, we've got it. The g- future is gonna be glorious.”Sarah Guo: Uh, you kind of have to deliver tangible benefits. Um, and quite frankly, politicians winning elections, uh, because they have advocated for that. That will be at least my adjustment because without it, um, thinking that somehow... Because it's too important this time around. It's too much of the economy for it not to be the case So one very simple framework I have for, you know, what are, what is gonna be the broad benefit of AI, um, beyond the communities just working in technology, are, are sort of wealth creation- Yepit's [00:37:00] gonna happen in a ton of different companies, startups and large companies. Then you have healthcare. Uh, you, you had amazing demos today. There are companies like Open Evidence. I think that is happening. Um,Education & Future of LearningSarah Guo: education seems like another one that's an- Yep ... obvious good where we haven't seen as much impact as I'd expect.Swyx: Do you have a hypothesis on why that might be, or if it'll come? Yeah, I mean, I think this is where, again, how we think about education, how... You know, recently I met with, uh, the founders of Alpha School and learnt a lot about what they were going and going about, and it's fascinating to listen, uh, to how to even rethink- MmSatya Nadella: uh, what does education really look like. Because I think it's actually very important. Mm. Uh, and I'm not saying anything traditionally being done is less important, right? I was even looking at the, uh... It's fascinating to see. I, I, I forget the which Stanford class it was, uh, the, the Asian guidelines for CS something.Mm. Uh, because you still need people to learn. Uh, like it was an interesting AI class that they were making sure people were learning how to apply softmax appropriately versus saying, “Hey, fix my training run.” Mm-hmm. Uh, so I think learning concepts is important. It's going to [00:38:00] be, uh, critical. But the way we create the incentives, what are the credentials, how we value those credentials, what is the employment opportunity for those credentials?So I think that there's a complete change that has to happen, uh, given the way to get to information, way to educate yourself, way to continuously keep yourself updated has changed so much. So I think interestingly enough, maybe the next big startup and success story could be someone who builds a new university, um, or a new, um, pedagogy even of how to get someone to go through a curriculum and find economic opportunity, uh, that's highly valuable.Well, that has felt, uh, perhaps impossible for a long time, but it's a great note to end on and something that might be possible. It's still possible. Yeah. Thank you, Satya. Thank you so much. Thank you. Yeah. I appreciate it. Thank you all. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

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/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 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.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/