DP-600 Exam Dumps : Implementing Analytics Solutions Using Microsoft Fabric

You need to recommend which type of Fabric capacity SKU meets the data analytics requirements for the Research division.

Requirement: “The Research division workspaces must use a dedicated, on-demand capacity that has per-minute billing.”

Fabric capacity SKUs:

F (Fabric) = dedicated Fabric capacity, available on pay-as-you-go with per-minute billing.

P (Premium) and EM are Power BI capacities (not Fabric-native).

A refers to Azure Analysis Services capacity.

The only correct option is F SKU.

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

When you need to return all rows that are present in both tables, you use a full outer join. This type of join combines the results of both left and right outer joins and returns all rows from both tables, with matching rows from both sides where available. If there is no match, the result is NULL on the side of the join where there is no match.