You have built a lakehouse in Microsoft Fabric. The notebooks are in place, data is flowing through the layers, and transformations are working. Now comes the hard question: how do you orchestrate it all, reliably, scalably, and in a way that fits real-world workloads?

Should you use Data Factory pipelines, notebook-driven orchestration, materialized views, or bring in a third-party orchestration tool? Each option has clear strengths, but also trade-offs that can become painful in production if chosen incorrectly.

In this session, we take a deep, practical dive into the orchestration options available for Fabric lakehouses. We will break down how each approach actually works, where it excels, where it falls short, and, most importantly, when you should use one over the others. Through concrete scenarios and production-proven examples, we will compare orchestration patterns for batch processing, dependencies, retries, monitoring, and operational complexity.

This is not a theoretical discussion. The session is grounded in real implementations used in production Fabric environments, including the challenges, pitfalls, and lessons learned along the way.

After attending this session, you will leave with a clear decision framework for choosing the right orchestration strategy for your Fabric lakehouse, confidently and deliberately, rather than by trial and error.