You have a Fabric tenant that uses a Microsoft tower Bl Premium capacity. You need to enable scale-out for a semantic model. What should you do first?

• A.At the tenant level, set Create and use Metrics to Enabled.
• B.At the semantic model level, set Large dataset storage format to On.
• C.At the semantic model level, set Large dataset storage format to Off.
• D.At the tenant level, set Data Activator to Enabled.

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You have a Microsoft Power Bl semantic model.
You plan to implement calculation groups.
You need to create a calculation item that will change the context from the selected date to month-to-date (MTD).
How should you complete the DAX expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

To create a calculation item that changes the context from the selected date to month-to-date (MTD), the appropriate DAX expression involves using the CALCULATE function to alter the filter context and the DATESMTD function to specify the month-to-date context.
The correct completion for the DAX expression would be:
* In the first dropdown, select CALCULATE.
* In the second dropdown, select SELECTEDMEASURE.
This would create a DAX expression in the form:
CALCULATE(
SELECTEDMEASURE(),
DATESMTD('Date'[DateColumn])
)

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You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD).
Which two actions should you include in the process? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.

• A.Insert new records when the natural key is a new value in the table.
• B.Update the effective end date of rows when the non-key attribute values have changed.
• C.Insert new rows when the natural key exists in the dimension table, and the non-key attribute values have changed.
• D.Update rows when the non-key attributes have changed.

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You have a Fabric tenant tha1 contains a takehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer.
When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table.
You need to identify whether maintenance tasks were performed on Customer.
Solution: You run the following Spark SQL statement:
EXPLAIN TABLE customer
Does this meet the goal?

• A.No
• B.Yes

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You have a Fabric tenant that contains a warehouse.
Several times a day. the performance of all warehouse queries degrades. You suspect that Fabric is throttling the compute used by the warehouse.
What should you use to identify whether throttling is occurring?

• A.dynamic management views (DMVs)
• B.the Monitoring hub
• C.the Microsoft Fabric Capacity Metrics app
• D.the Capacity settings

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