Philip Seamark
dax.tips
Member of the Power BI CAT team. Focused on helping people learn data modelling and DAX on the MSFT BI Stack
SQLBits 2024
Microsoft Fabric Power BI DirectLake Deep Dive
In this session you will learn all you need to know about DirectLake, how does it work? What is the difference with import? We will get you ready to decide if you should use DirectLake for your new project and what all the things you should know for your project.
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. One of the most exciting new features that come with Fabric is DirectLake. DirectLake is a fast path to load the data from the data lake straight into the Power BI engine, immediately ready for analysis.
In this session we get you ready to decide if you should use DirectLake for your new project and what all the things you should know for your project.
First, we will 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. Then we will dive deep into DirectLake. How is this data being exposed to Power BI through Directlake and how this differs from DirectQuery or Import? How can we use RLS security to protect our data? Then we'll solve some traditional BI patterns like incremental refresh and transactions on top of data getting loaded into the Fabric lakehouse. Then we'll talk about how to get the best performance and show you all the steps to debug this.
At the end of this session, you are ready to tackle any new DirectLake session
In this session we get you ready to decide if you should use DirectLake for your new project and what all the things you should know for your project.
First, we will 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. Then we will dive deep into DirectLake. How is this data being exposed to Power BI through Directlake and how this differs from DirectQuery or Import? How can we use RLS security to protect our data? Then we'll solve some traditional BI patterns like incremental refresh and transactions on top of data getting loaded into the Fabric lakehouse. Then we'll talk about how to get the best performance and show you all the steps to debug this.
At the end of this session, you are ready to tackle any new DirectLake session