Choosing the Right Incremental Load Strategy in Fabric

Incremental loading has been around for years as a way to keep data pipelines efficient and cost-effective. But what does it look like in Microsoft Fabric, and how can you pick the best approach for your needs?
In this session, we’ll explore how to implement incremental loads in Fabric and, more importantly, how to choose the right strategy for your scenario. We’ll compare different approaches, including CopyJobs, Dataflow Gen2, Notebooks, and Mirroring, highlighting their strengths, limitations, and best-fit use cases.
You’ll learn:
- Why incremental loading is critical for performance and cost optimization
- How to use Fabric’s tools to set up incremental loads that work for large datasets and growing environments
- Practical demos to get you started quickly

By the end of this session, you’ll know how to apply incremental loading in Microsoft Fabric and confidently choose the right approach for your data pipelines.

By the end of this session, you’ll know how to apply incremental loading in Microsoft Fabric and confidently choose the right approach for your data pipelines.