If you’ve set up row level security in Power BI before, you know the usual drill: open the semantic model, add a role, write a DAX filter. But once your data lives inside a Microsoft Fabric OneLake structure, there’s a better way to do this. You can implement it directly in OneLake instead, so that every object built on top of that data, your lakehouse, your SQL analytics endpoint, your semantic model, and your report, all follow the same security setup automatically. Define it once, upstream, and everything downstream inherits it. This is called OneLake security, and in this post I’ll walk through exactly how to set up row level security (RLS) this way, from the lakehouse all the way to your Power BI report.
Read on for a video and summary with timestamps.