Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You administer a Microsoft Fabric workspace that contains a lakehouse with several Delta tables used by multiple analytics teams. You must ensure that data analysts can query the SalesOrders table but must never see rows where the column TerritoryID equals 60. Business analysts should have unrestricted access. You need to configure this requirement in the most granular and performant way without duplicating data or creating additional views. Which approach should you implement in the lakehouse?
Publish a Power BI semantic model on top of SalesOrders and use that model's row-level security instead of configuring security in the lakehouse.
Create a row-level security policy on the SalesOrders Delta table that filters out rows with TerritoryID = 60 for the data-analysts security group.
Move SalesOrders to a separate folder secured with OneLake folder permissions that exclude the data-analysts group.
Grant the data-analysts group the Viewer role on the lakehouse and deny them access to the TerritoryID column by defining column-level security.
In a lakehouse, Delta tables are queried through Apache Spark or the SQL analytics endpoint. The most granular way to hide specific rows from a subset of users-without copying data or creating separate views-is to create a Row-Level Security (RLS) policy on the Delta table. RLS filters rows at query time based on predicates tied to user identities, so data analysts querying SalesOrders will automatically be prevented from seeing rows where TerritoryID = 60. Workspace roles alone cannot filter individual rows because they apply permissions at the item (object) level only. Column-level security targets specific columns, not rows. Converting the table to a secured Power BI semantic model would introduce an additional object and require separate maintenance, which is unnecessary when RLS can be applied directly on the Delta table.
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Microsoft Fabric Data Engineer Associate DP-700
Implement and manage an analytics solution
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