Explanation:

To implement row-level security (RLS) in a Fabric Warehouse (like in Azure Synapse or SQL Server):
You must define a predicate function (usually an inline table-valued function) that filters rows for each user # Function.
Then you bind that function to the table using a Security Policy # Security Policy.
A Database Role is used for group-based access control but not specifically for implementing RLS.
Stored procedures and constraints are not used for RLS.
Correct answers: A and D
Reference: Row-Level Security (RLS) in Synapse/Fabric SQL

No, the EXPLAIN TABLE statement does not identify whether maintenance tasks were performed on a table.
It shows the execution plan for a query. References = The usage and output of the EXPLAIN command can be found in the Spark SQL documentation.

Explanation:
The correct order for the DAX expression would be:
DEFINE VAR _SalesSince = DATE ( 2023, 12, 01 )
EVALUATE
FILTER (
SUMMARIZE ( Store, Store[Name], Store[OpenDate] ),
Store[OpenDate] > = _SalesSince )
In this DAX query, you ' re defining a variable _SalesSince to hold the date from which you want to filter the stores. EVALUATE starts the definition of the query. The FILTER function is used to return a table that filters another table or expression. SUMMARIZE creates a summary table for the stores, including the Store
[Name] and Store[OpenDate] columns, and the filter expression Store[OpenDate] > = _SalesSince ensures only stores opened on or after December 1, 2023, are included in the results.
References =
DAX FILTER Function
DAX SUMMARIZE Function

Explanation: