M365 Show with Mirko Peters - Microsoft 365 Digital Workplace Daily cover art

M365 Show with Mirko Peters - Microsoft 365 Digital Workplace Daily

M365 Show with Mirko Peters - Microsoft 365 Digital Workplace Daily

By: Mirko Peters - Microsoft 365 Expert Podcast
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 The M365 Show – Microsoft 365, Azure, Power Platform & Cloud Innovation Stay ahead in the world of Microsoft 365, Azure, and the Microsoft Cloud. The M365 Show brings you expert insights, real-world use cases, and the latest updates across Power BI, Power Platform, Microsoft Teams, Viva, Fabric, Purview, Security, AI, and more. Hosted by industry experts, each episode features actionable tips, best practices, and interviews with Microsoft MVPs, product leaders, and technology innovators. Whether you’re an IT pro, business leader, developer, or data enthusiast, you’ll discover the strategies, trends, and tools you need to boost productivity, secure your environment, and drive digital transformation. Your go-to Microsoft 365 podcast for cloud collaboration, data analytics, and workplace innovation. Tune in, level up, and make the most of everything Microsoft has to offer. Visit M365.show.

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Episodes
  • How Data Goblins Wreck Copilot For Everyone

    How Data Goblins Wreck Copilot For Everyone
    Sep 23 2025
    Picture your data as a swarm of goblins: messy, multiplying in the dark, and definitely not helping you win over users. Drop Copilot into that chaos and you don’t get magic productivity—you get it spitting out outdated contract summaries and random nonsense your boss thinks came from 2017. Not exactly confidence-inspiring. Here’s the fix: tame those goblins with the right prep and rollout, and Copilot finally acts like the assistant people actually want. I’ll give you the Top 10 actions to make Copilot useful, not theory—stuff you can run this week. Quick plug: grab the free checklist at m365.show so you don’t miss a step. Because the real nightmare isn’t day two of Copilot. It’s when your rollout fails before anyone even touches it.Why Deployments Fail Before Day OneToo many Copilot rollouts sputter out before users ever give it a fair shot. And it’s rarely because Microsoft slipped some bad code into your tenant or you missed a magic license toggle. The real problem is expectation—people walk in thinking Copilot is a switch you flip and suddenly thirty versions of a budget file merge into one perfect answer. That’s the dream. Reality is more like trying to fuel an Olympic runner with cheeseburgers: instead of medals, you just get cramps and regret. The issue comes down to data. Copilot doesn’t invent knowledge; it chews on whatever records you feed it. If your tenant is a mess of untagged files, duplicate spreadsheets, and abandoned SharePoint folders, you’ve basically laid out a dumpster buffet. One company I worked with thought their contract library was “clean.” In practice, some contracts were expired, others mislabeled, and half were just old drafts stuck in “final” folders. The result? Copilot spat out a summary confidently claiming a partnership from 2019 was still active. Legal freaked out. Leadership panicked. And trust in Copilot nosedived almost instantly. That kind of fiasco isn’t on the AI—it’s on the inputs. Copilot did exactly what it was told: turn garbage into polished garbage. The dangerous part is how convincing the output looks. Users hear the fluent summary and trust it, right up until they find a glaring contradiction. By then, the tool carries a new label: unreliable. And once that sticker’s applied, it’s hard to peel off. Experience and practitioner chatter all point to the same root problem: poor data governance kills AI projects before they even start. You can pay for licenses, bring in consultants, and run glossy kickoff meetings. None of it matters if the system underneath is mud. And here’s the kicker—users don’t care about roadmap PowerPoints or governance frameworks. If their very first Copilot query comes back wrong, they close the window and move on. From their perspective, the pitch is simple: “Here’s this fancy new assistant. Ask it anything.” So they try something basic like, “Show me open contracts with supplier X.” Copilot obliges—with outdated deals, missing clauses, and expired terms all mixed in. Ask yourself—would they click a second time after that? Probably not. As soon as the office rumor mill brands it “just another gimmick,” adoption flatlines. So what’s the fix? Start small. Take that first anecdote: the messy contract library. If it sounds familiar, don’t set out to clean your entire estate. Instead, triage. Pick one folder you can fix in two days. Get labels consistent, dates current, drafts removed. Then connect Copilot to that small slice and run the same test. The difference is immediate—and more importantly, it rebuilds user confidence. Think of it like pest control. Every missing metadata field, every duplicate spreadsheet, every “Final_V7_REALLY.xlsx” is another goblin running loose in the basement. Leadership may be upstairs celebrating their shiny AI pilot, but downstairs those goblins are chewing wires and rearranging folders. Let Copilot loose down there, and you’ve just handed them megaphones. The takeaway is simple: bad data doesn’t blow up your deployment in one dramatic crash. It just sandpapers every interaction until user trust wears down completely. One bad answer becomes two. Then the whispers start: “It’s not accurate.” Soon nobody bothers to try it at all. So the hidden first step isn’t licensing or training—it’s hunting the goblins. Scrub a small set of records. Enforce some structure. Prove the tool works with clean inputs before scaling out. Skip that, and yes—your rollout fails before Day One. But there’s another side to this problem worth calling out. Even if the data is ready, users won’t lean in unless they actually *want* to. Which raises the harder question: why would someone ask for Copilot at all, instead of just ignoring it?How Organizations Got People to *Want* CopilotWhat flipped the script for some organizations was simple: they got people to *want* Copilot, not just tolerate it. And that’s rare in IT land. Normally,...
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    18 mins
  • GitHub, Azure DevOps, or Fabric—Who’s Actually in Charge?

    GitHub, Azure DevOps, or Fabric—Who’s Actually in Charge?
    Sep 22 2025
    Here’s a statement that might sting: without CI/CD, your so‑called Medallion Architecture is nothing more than a very expensive CSV swamp. Subscribe to the M365.Show newsletter so you i can reach Gold Medallion on Substack!Now, the good news: we’re not here to leave you gasping in that swamp. We’ll show a practical, repeatable approach you can follow to keep Fabric Warehouse assets versioned, tested, and promotable without midnight firefights. By the end, you’ll see how to treat data pipelines like code, not mystery scripts. And that starts with the first layer, where one bad load can wreck everything that follows.Bronze Without Rollback: Your CSV GraveyardPicture this: your Bronze layer takes in corrupted data. No red lights, no alarms, just several gigabytes of garbage neatly written into your landing zone. What do you do now? Without CI/CD to protect you, that corruption becomes permanent. Worse, every table downstream is slurping it up without realizing. That’s why Bronze so often turns into what I call the CSV graveyard. Teams think it’s just a dumping ground for raw data, but if you don’t have version control and rollback paths, what you’re really babysitting is a live minefield. People pitch Bronze as the safe space: drop in your JSON files, IoT logs, or mystery exports for later. Problem is, “safe” usually means “nobody touches it.” The files become sacred artifacts—raw, immutable, untouchable. Except they’re not. They’re garbage-prone. One connector starts spewing broken timestamps, or a schema sneaks in three extra columns. Maybe the feed includes headers some days and skips them on others. Weeks pass before anyone realizes half the nightly reports are ten percent wrong. And when the Bronze layer is poisoned, there’s no quick undo. Think about it: you can’t just Control+Z nine terabytes of corrupted ingestion. Bronze without CI/CD is like writing your dissertation in one single Word doc, no backups, no versions, and just praying you don’t hit crash-to-desktop. Spoiler alert: crash-to-desktop always comes. I’ve seen teams lose critical reporting periods that way—small connector tweaks going straight to production ingestion, no rollback, no audit trail. What follows is weeks of engineers reconstructing pipelines from scratch while leadership asks why financials suddenly don’t match reality. Not fun. Here’s the real fix: treat ingestion code like any other codebase. Bronze pipelines are not temporary throwaway scripts. They live longer than you think, and if they’re not branchable, reviewable, and version-controlled, they’ll eventually blow up. It’s the same principle as duct taping your car bumper—you think it’s temporary until one day the bumper falls off in traffic. I once watched a retail team load a sea of duplicated rows into Bronze after an overnight connector failure. By the time they noticed, months of dashboards and lookups were poisoned. The rollback “process” was eight engineers manually rewriting ingestion logic while trying to reload weeks of data under pressure. That entire disaster could have been avoided if they had three simple guardrails. Step one: put ingestion code in Git with proper branching. Treat notebooks and configs like real deployable code. Step two: parameterize your connection strings and schema maps so you don’t hardwire production into every pipeline. Step three: lock deployments behind pipeline runs that validate syntax and schema before touching Bronze. That includes one small but vital test—run a pre-deploy schema check or a lightweight dry‑run ingestion. That catches mismatched timestamps or broken column headers before they break Bronze forever. Now replay that earlier horror story with these guardrails in place. Instead of panicking at three in the morning, you review last week’s commit, you roll back, redeploy, and everything stabilizes in minutes. That’s the difference between being crushed by Bronze chaos and running controlled, repeatable ingestion that you trust under deadline. The real lesson here? You never trust luck. You trust Git. Ingestion logic sits in version control, deployments run through CI/CD with schema checks, and rollback is built into the process. That way, when failure hits—and it always does—you’re not scrambling. You’re reverting. Big difference. Bronze suddenly feels less like Russian roulette and more like a controlled process that won’t keep you awake at night. Fixing Bronze is possible with discipline, but don’t take a victory lap yet. Because the next layer looks polished, structured, and safe—but it hides even nastier problems that most teams don’t catch until the damage is already done.Silver Layer: Where Governance Dies QuietlyAt first glance, Silver looks like the clean part of the Warehouse. Neat columns, standard formats, rows aligned like showroom furniture. But this is also where governance takes the biggest hit—because the mess ...
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    18 mins
  • Your Power Automate Approval Flow Isn’t Audit-Proof

    Your Power Automate Approval Flow Isn’t Audit-Proof
    Sep 22 2025
    Here’s the catch Microsoft doesn’t highlight: Power Automate’s run history is time‑limited by default. Retention depends on your plan and license, and it’s not forever. Once it rolls off, it’s gone—like it never ran. Great for Microsoft’s servers. Terrible for your audit trail. Designing without logging is like deleting your CCTV before the cops arrive. You might think you’re fine until someone actually needs the footage. Today we’ll show you how to log approvals permanently, restart flows from a stage, use dynamic approvers, and build sane escalations and reminders. Subscribe to the newsletter at m365 dot show if you want blunt fixes, not marketing decks. Because here’s the question you need to face—think your workflow trail is permanent? Spoiler: it disappears faster than free donuts in the break room.Why Your Flow History VanishesSo let’s get into why your flow history quietly disappears in the first place. You hit save on a flow, you check the run history tab, and you think, “Perfect. There’s my record. Problem solved.” Except that little log isn’t built to last. It’s more like a Post-it note on the office fridge—looks useful for a while, but it eventually drops into the recycling bin. Here’s the truth: Power Automate isn’t giving you a permanent archive. It’s giving you temporary storage designed with Microsoft’s servers in mind—not your compliance officer. How long your runs stay visible varies by plan and license. If you want the specifics, check your tenant settings or Microsoft’s own documentation. I’ll link the official retention guidance in the notes—verify your setup, because what you see depends entirely on your license. Most IT teams assume “cloud equals forever.” Microsoft assumes “forever equals a storage nightmare.” So they quietly clean house. That’s the built-in expectation: logs expire, data rolls off, and your history evaporates. They’re doing housekeeping. You’re the one left without receipts when auditors come calling. Let’s bring it into real life. Imagine HR asks for proof of a promotion approval from last year. Fourteen months ago, your director clicked Approve, everyone celebrated, and the process moved on. Fast forward, compliance wants records. You open Power Automate, dig into runs... and there’s nothing left. That tidy approval trail you trusted has already been vacuumed away. That’s not Microsoft failing to tell you. It’s right there in the docs—you just don’t see it unless you squint through the licensing fine print. They’re clear they’re not your compliance archive. That’s your job. And if you walk into an audit with holes in your data, the meeting isn’t going to be pleasant. Now picture this: it’s like Netflix wiping your watch history every Monday. One week you know exactly where you paused mid-season. Next week? Gone. The system pretends you never binged a single show. That’s how absurd it looks when an auditor asks for approval records and your run history tab is empty. The kicker is the consequences. Missing records isn’t just a mild inconvenience. Failing to show documentation can trigger compliance reviews and consequences that vary by regulation—and if you’re in a regulated industry, that can get expensive very quickly. And even if regulators aren’t involved, leadership will notice. You were trusted to automate approvals. If you can’t prove past approvals existed, congratulations—you’re now the weak link in the chain. And no, screenshots don’t save you. Screenshots are like photos of your dinner—you can show something happened, but you can’t prove it wasn’t staged. Auditors want structured data: dates, times, names, decisions. All the detail that screenshots can’t provide. And that doesn’t live in the temporary run history. Here’s a quick reality check you can do right now. Pause this video, go into Power Automate, click “My flows,” open run history on one of your flows, and look for the oldest available run. That’s your retention window. If it’s missing approvals you thought were permanent, you’ve already felt the problem firsthand. Want to know the one-click way to confirm exactly what your tenant holds? Stick around—I’ll show you in the checklist. So where does this leave you? Simple: if you don’t build logging into your workflows, you don’t have approval history at all. Pretending defaults are enough is like trusting a teenager when they say they cleaned their room—by Monday the mess will resurface, and nothing important will have survived. The key takeaway: Power Automate run history is a debugging aid, not a record keeper. It’s disposable by design, not permanent or audit-ready. If you want usable records, you have to create your own structured logs outside that temporary buffer. And this isn’t just about saving history. Weak logging means fragile workflows, and fragile workflows collapse the first time you push ...
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    20 mins
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