Mastering AI in Power BI
Proposed session for SQLBits 2026TL; DR
A full end-to-end masterclass on AI in Power BI. During this training day, we’ll cover every corner of AI in Power BI, from preparing data for AI to bringing your Power BI AI assets to life with AI.
Session Details
A full end-to-end masterclass on AI in Power BI. During this training day, we’ll cover every corner of AI in Power BI, from preparing data for AI to bringing your Power BI AI assets to life with MCP.
In these times, AI literacy is both an essential career skill and a powerful value-add for organizations. The ability to quickly and easily draw insights and get answers from our data is as important as ever. Furthermore, being able to interact with our data through conversational communication is increasingly in demand.
The training day will be a mix of presentation-style teaching, interactive exercises, and workshop labs. After attending this training day, you’ll be able to set up everything around AI in Power BI end-to-end. You’ll be up to date on the newest tools for AI-powered BI—ready to develop solutions or advise clients and colleagues on how to use AI with Power BI.
Module 1: Data Prep for AI – with AI
In this module, we’ll explore how to get your data ready for AI usage. We’ll cover semantic modeling best practices, context- and prompt engineering, and how to leverage AI itself to fine-tune semantic models for AI usage.
Module 2: AI-assisted Power BI development
In this module, we'll explore the various options for improving your development productivity with the available AI toolbox. We'll cover how the built-in Copilot may help improve low-code workflows and move on to full-fledged AI coding agents. At this stage, participants will learn how to make AI agents develop whole user stories with no human involvement.
Module 3: Data Agents
The third module covers everything about using semantic models as assets for AI agents. In this module, you'll learn how to set up, configure, and refine data agents so that your semantic model data is readily available for "chat with your data" scenarios, as well as for use outside of Power BI.
Module 4: External solutions
In the final module, we explore how Power BI data can be used with AI tools outside of Power BI itself. We'll cover how to use MCP to create custom AI agents and how to use the native MCPs for quick results. Furthermore, we'll explore how to integrate your data agents and semantic models with the rest of the Microsoft AI ecosystem, using AI Foundry and Copilot Studio. Finally, we'll cover how to move beyond the boundaries of Microsoft and use the data in cloud-agnostic use cases, using today's most talked-about AI tools.
In these times, AI literacy is both an essential career skill and a powerful value-add for organizations. The ability to quickly and easily draw insights and get answers from our data is as important as ever. Furthermore, being able to interact with our data through conversational communication is increasingly in demand.
The training day will be a mix of presentation-style teaching, interactive exercises, and workshop labs. After attending this training day, you’ll be able to set up everything around AI in Power BI end-to-end. You’ll be up to date on the newest tools for AI-powered BI—ready to develop solutions or advise clients and colleagues on how to use AI with Power BI.
Module 1: Data Prep for AI – with AI
In this module, we’ll explore how to get your data ready for AI usage. We’ll cover semantic modeling best practices, context- and prompt engineering, and how to leverage AI itself to fine-tune semantic models for AI usage.
Module 2: AI-assisted Power BI development
In this module, we'll explore the various options for improving your development productivity with the available AI toolbox. We'll cover how the built-in Copilot may help improve low-code workflows and move on to full-fledged AI coding agents. At this stage, participants will learn how to make AI agents develop whole user stories with no human involvement.
Module 3: Data Agents
The third module covers everything about using semantic models as assets for AI agents. In this module, you'll learn how to set up, configure, and refine data agents so that your semantic model data is readily available for "chat with your data" scenarios, as well as for use outside of Power BI.
Module 4: External solutions
In the final module, we explore how Power BI data can be used with AI tools outside of Power BI itself. We'll cover how to use MCP to create custom AI agents and how to use the native MCPs for quick results. Furthermore, we'll explore how to integrate your data agents and semantic models with the rest of the Microsoft AI ecosystem, using AI Foundry and Copilot Studio. Finally, we'll cover how to move beyond the boundaries of Microsoft and use the data in cloud-agnostic use cases, using today's most talked-about AI tools.
3 things you'll get out of this session
- Learning to prepare current data estate for AI
- Accelerating development with AI tools
- Learning every ins and outs of Fabric Data Agents
- Create and use Fabric Data Agents themselves
- Bringing data and agents alive outside of Power BI / Fabric
Speakers
Mathias Halkjaer's other proposed sessions for 2026
Beware! SQL Injection through ADF/Pipelines - 2026
Fabric Data Agents and beyond - 2026
Ingesting API data with Python Notebooks - 2026
Mastering Direct Lake - 2026
Navigating Data Modeling in Direct Lake - 2026
The Future of Data - 2026
Vibecoding examples for data professionals - 2026
Vibe-coding for the data professional - 2026
When data lies - typical patterns for manipulating data - 2026
Mathias Halkjaer's previous sessions
Nose-Dive Narratives: Slide Karaoke 2024
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A deep dive into Direct Lake
The new Direct Lake storage mode in Power BI promises to revolutionize data handling by blending the real-time nature of DirectQuery and the high performance of Import mode. Is this all just hype, or does Direct Lake truly deliver on these claims?