As semantic models grow in size and complexity, performance, memory usage, and refresh times quickly become the biggest challenges in Microsoft Fabric.

In this advanced, hands-on workshop, we go beyond best practices and dive deep into how the VertiPaq engine behaves under real-world pressure. You will learn how to diagnose bottlenecks, reduce model size, and optimize performance using proven techniques from large-scale enterprise solutions.

We will explore topics such as column cardinality, encoding strategies, memory consumption patterns, and how different storage modes—including Direct Lake—impact performance and scalability.

You will also learn how to design efficient refresh strategies, avoid common pitfalls that lead to paging and memory pressure, and understand how query patterns affect performance.

Through guided exercises, you will work with intentionally inefficient models and transform them into optimized, production-ready solutions.

This workshop is based on real-world experience optimizing semantic models in Microsoft Fabric and Power BI at scale.

If you are working with large or complex models and want to push performance to the next level, this session is for you.