Microsoft Fabric, Lakehouses and Power BI: A guide for BI developers

Microsoft Fabric is here, and it fundamentally changes our data landscape. It introduces a Power BI like SaaS model for the data platform. You can now with a few clicks ingest data into the cloud by running pipelines, create a Lakehouse to make that data accessible and run Python, Spark, SQL and DAX on top of it. What does this all mean for Power BI? There are a lot of architectural changes, and you might wonder if you now need to start refactoring your Power BI solutions.

In this session we get you ready to decide whether you want to start using the new Fabric workloads for your Power BI solutions. First, we do an introduction of Microsoft Fabric is, then we will get an overview of lakehouse and how the data is stored in parquet files under the covers. Finally, we will see how this data is being exposed to Power BI through Directlake and how this differs from DirectQuery or Import. Then we will close off with demos where we solve some common Power BI patterns like incremental refresh and transactions on top of data getting loaded into the Fabric lakehouse.

Kasper de Jonge

Principal Program Manager, MS Power BI

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