Free Access Microsoft.DP-600.v2026-07-08.q133 Practice Test (Page 22)

Question 101

You have a Fabric workspace named Workspace1.
Workspace1 contains multiple semantic models, including a model named Model1. Model1 is updated by using an XMLA endpoint.
You need to increase the speed of the write operations of the XMLA endpoint.
What should you do?

A.Select Large semantic model storage format for Workspace1.

B.Configure Model1 to use the Direct Lake storage format.

C.Delete any unused semantic models from Workspace1.

D.Delete any unused columns from Model1.

Correct Answer: A

When using XMLA endpoints to manage and update semantic models in Microsoft Fabric, the performance of write operations (such as processing, structural changes, or metadata deployments from Tabular Editor) is directly influenced by the storage format and how the model is persisted.
Why Option A is Correct
* By default, Fabric semantic models use the Small semantic model storage format.
* To improve write operations performance through XMLA, you must change the workspace setting to use the Large semantic model storage format.
* The large format uses more efficient storage techniques, supports partitioning, and handles larger models with optimized write capabilities.
* This setting is applied at the workspace level and impacts all semantic models within that workspace, including Model1.
This is explicitly documented in Microsoft's guidance: Large semantic model storage format is required when using XMLA write operations for large or frequently updated models.
Why the Other Options Are Incorrect
B). Configure Model1 to use the Direct Lake storage format.
* Direct Lake mode is designed for query performance (reading data directly from OneLake in delta format without import/duplication).
* It improves query latency and freshness but does not improve XMLA write operations, which deal with model metadata and structural updates.
C). Delete any unused semantic models from Workspace1.
* Deleting unused semantic models helps manage capacity and storage but does not increase the speed of XMLA endpoint write operations.
* Workspace storage overhead does not directly impact the write throughput of XMLA operations.
D). Delete any unused columns from Model1.
* Removing unused columns reduces the memory footprint and can improve query performance.
* However, it does not directly improve the speed of XMLA write operations. The bottleneck in XMLA writes is tied to the storage format, not the model size alone.
Summary
To increase the speed of XMLA write operations on semantic models, you must enable the Large semantic model storage format at the workspace level. This setting ensures better handling of writes and metadata operations via the XMLA endpoint.
References
* Large models in Power BI and Microsoft Fabric
* Use the XMLA endpoint in Microsoft Fabric
* Manage capacities in Microsoft Fabric

Question 102

You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1. Report1 includes a Python visual. Data displayed by the visual is grouped automatically and duplicate rows are NOT displayed. You need all rows to appear in the visual. What should you do?

A.Reference the columns in the Python code by index.

B.Modify the Sort Column By property for all columns.

C.Add a unique field to each row.

D.Modify the Summarize By property for all columns.

Question 103

You have a Fabric tenant that contains a workspace named Workspace1.
You plan to deploy a semantic model named Model1 by using the XMLA endpoint.
You need to optimize the deployment of Model1. The solution must minimize how long it takes to deploy Model1.
What should you do in Workspace1?

A.Select Small semantic model storage format.

B.Select Users can edit data models in the Power BI service.

C.Set Enable Cache for Shortcuts to On.

D.Select Large semantic model storage format.

Question 104

You have a Microsoft Power Bl project that contains a file named definition.pbir. definition.pbir contains the following JSON.

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Question 105

You have a Fabric workspace that uses the default Spark starter pool and runtime version 1,2.
You plan to read a CSV file named Sales.raw.csv in a lakehouse, select columns, and save the data as a Delta table to the managed area of the lakehouse. Sales_raw.csv contains 12 columns.
You have the following code.