Nicky van Vroenhoven

Power BI used to be a tool you clicked your way through. Then PBIP turned your semantic models and reports into plain text (TMDL, JSON), and suddenly an entirely different toolbox showed up at the door: AI agents that can read, write, and reason about your model the same way they reason about code. This session is about what happens once you let those agents in. Not the marketing kind of "AI in Power BI", but the practical, sometimes scrappy, often surprisingly powerful kind: GitHub Copilot in agent mode, working on your PBIP files, with the right context loaded, the right skills wired up, and the right MCPs connecting it to Fabric. We'll start with a quick tour of why PBIP matters and what an "agent" actually is in this context. From there we go hands-on. Expect a lot of demos: Copilot writing DAX in TMDL, generating documentation, doing bulk model edits, reviewing pull requests, and chaining all of it together into workflows that feel a lot less like clicking and a lot more like delegating. We'll wire up an MCP so Copilot can talk to Power BI Desktop directly, and we'll show what changes when your agent stops guessing and starts looking things up. Throughout, we'll keep one question front and center: where does the agent earn its keep, and where is it still happily wrong with confidence? You'll leave with a clear sense of what's real today and a workflow you can replicate on Monday morning.

The term storage mode in Power BI refers to how tables are stored and how queries will be sent to the data source. In Power BI desktop you can specify the storage mode on a per-table basis.

You're part of an analytics team at a fast-growing tech company, relying on Power BI for key insights. But as your data and team grow, so do the challenges: messy files, unclear version history, and unwieldy data models. Then inspiration strikes - another team solved similar issues by adopting a structured project setup, using source control, and managing models with TMDL. You follow their lead. Months later, your workflow is streamlined, collaboration is smooth, and your reports are sharper than ever. This session shares the strategies that made that transformation possible - so you can apply them in your own Power BI projects. In this session, we will guide you through these strategies, demonstrating how to replicate this success in your own Power BI projects. By the end of this session, you will be equipped with practical knowledge and tools to optimize their Power BI workflows, ensuring their data analytics projects are well-organized, versioned, and scalable. We will start with a regular PBIX-file and gradually transform it into an organized, versioned model. Using Visual Studio Code, we will set up source control in Azure DevOps with the PBIP-format, apply TMDL and eventually integrate Git into the workspace. Note: This session assumes a basic understanding of Power BI. Fundamentals of source control and branching will not be covered.

Imagine you're part of a dynamic analytics team at a rapidly growing tech company. Your team relies heavily on Power BI to create insightful reports and dashboards that drive key business decisions.

Do you know your way around Power BI Desktop, but don't know what happens beyond it, or what has to be managed in the Service? Did you just receive the responsibility for some, or even all, Fabric (formerly known as Power BI) Administrator tasks?

Do you know your way around Power BI Desktop, but don't know what happens beyond it, or what has to be managed in the Service? Do you have the privilege, as an IT Admin or Global Administrator, to "also take care of Power BI/Fabric"? Did you just receive the responsibility for some, or even all, Fabric Administrator tasks? Do you also not know what the Power Platform (management) truly encompasses? If you answer Yes to any of the questions above, this session is for you! And did you know a Premium Capacity is not a switch you turn on and just walk away from. It's like heating tomato soup in the microwave: if you don't pay attention, it becomes a mess very quickly. In this session, we will take a look at tasks and components that can be part of a Power BI Admin's daily routine. - The role of the Power BI Admin - Tenant settings - Handling My Workspace - Premium and Admin Monitoring - Power Platform Admin Center When you start applying the tips and tricks of this session, you will get a grip on your Fabric tenant and have happier users!

The term storage mode in Power BI refers to how tables are stored and how queries will be sent to the data source. In Power BI desktop you can specify the storage mode on a per-table basis.

Have you ever wondered why you can't edit your data in Power BI like in Excel? Now you can! Well, not directly in Power BI, but you can accomplish this with a Power App inside a Power BI report. In this session you will learn how to create a basic Power App and how to use that in the Power Apps visual in a Power BI report. You will learn how to connect Power BI and Power Apps together to update data in a database and display the results in Power BI. During the session, we will also run through different use cases where this can be brought to practice. This is an intermediate (Power BI) session, so experience with Power BI is assumed, prior experience with Power Apps is not necessarily needed.

Power Query allows you to extract and transform data from a variety of data sources. Have you ever experienced that the importing of data is slower than you expected? In most of those cases, query folding is not happening fully optimized. Query folding is important because it offloads data transformations to the source, instead of performing them in Power BI. Attend this session to learn how to ensure that you get all the performance improvements possible within your reports! As an added bonus, you will also learn in which cases query folding is not your best friend.