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Microsoft DP-600 Exam Practice Questions (P. 5)

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Question #21
You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 is assigned to a Fabric capacity.
You need to recommend a solution to provide users with the ability to create and publish custom Direct Lake semantic models by using external tools. The solution must follow the principle of least privilege.
Which three actions in the Fabric Admin portal should you include in the recommendation? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
  1. A
    From the Tenant settings, set Allow XMLA Endpoints and Analyze in Excel with on-premises datasets to Enabled.
  2. B
    From the Tenant settings, set Allow Azure Active Directory guest users to access Microsoft Fabric to Enabled.
  3. C
    From the Tenant settings, select Users can edit data model in the Power BI service.
  4. D
    From the Capacity settings, set XMLA Endpoint to Read Write.
  5. E
    From the Tenant settings, set Users can create Fabric items to Enabled.
  6. F
    From the Tenant settings, enable Publish to Web.

Correct Answer:
ACD
chatbot-img GPT-4o - Answer
To implement a solution that enables users to create and manage custom Direct Lake semantic models through external tools while maintaining least privilege, consider enabling XMLA Endpoints and setting them to Read . Write, which is essential for allowing these tools to interact fully with the data models. This also allows tools to publish and manage these models securely. Additionally, modifying tenant settings to allow for XMLA interaction and editing within the Fabric service involves essential configurations that support external analytical operations without compromising security. This configuration is aligned with the recommended settings to offer controlled, yet functional access.

Question #22
You are creating a semantic model in Microsoft Power BI Desktop.
You plan to make bulk changes to the model by using the Tabular Model Definition Language (TMDL) extension for Microsoft Visual Studio Code.
You need to save the semantic model to a file.
Which file format should you use?
  1. A
    PBIP
  2. B
    PBIX
  3. C
    PBIT
  4. D
    PBIDS

Correct Answer:
A
chatbot-img GPT-4o - Answer
When working with the Tabular Model Definition Language (TMDL) in Microsoft Visual Studio Code for modifications to a semantic model in Power BI Desktop, saving the model as a PBIX file is the appropriate format. PBIX files encompass the full specifications of your Power BI report and dataset which is essential when intending to persist changes or perform extensive model updates using TMDL. Though there might be confusion about other formats such as PBIP, for the direct usage of TMDL codes and integrating bulk changes, the PBIX format remains most effective and compatible.

Question #23
HOTSPOT -
You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains three schemas named schemaA, schemaB, and schemaC.
You need to ensure that a user named User1 can truncate tables in schemaA only.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Question #24
You plan to deploy Microsoft Power BI items by using Fabric deployment pipelines. You have a deployment pipeline that contains three stages named Development, Test, and Production. A workspace is assigned to each stage.
You need to provide Power BI developers with access to the pipeline. The solution must meet the following requirements:
Ensure that the developers can deploy items to the workspaces for Development and Test.
Prevent the developers from deploying items to the workspace for Production.
Follow the principle of least privilege.
Which three levels of access should you assign to the developers? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
  1. A
    Build permission to the production semantic models
  2. B
    Admin access to the deployment pipeline
  3. C
    Viewer access to the Development and Test workspaces
  4. D
    Viewer access to the Production workspace
  5. E
    Contributor access to the Development and Test workspaces
  6. F
    Contributor access to the Production workspace

Correct Answer:
ADE
chatbot-img GPT-4o - Answer
Correctly assigning access levels to developers in a Microsoft Power BI deployment pipeline setup requires a focused understanding of permissions relative to workspace exposure and deployment capabilities. Specifically, developers should be granted Contributor access to Development and Test workspaces (E) to enable deployment activities in these less critical environments, aligning with their roles. For the Production workspace, however, granting them Viewer access (D) is essential—it allows necessary visibility without the ability to deploy or alter the production environment, maintaining strict control over deployment integrity. This setup correctly implements the principle of least privilege by carefully delineating permissions without overextending access, which is crucial for maintaining both security and operational functionality.

Question #25
You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.
You have a Microsoft Power Bi report named Report1 that uses the model. Report1 contains visuals on multiple pages.
You need to reduce the query execution time for the visuals on all the pages.
What are two features that you can use? Each correct answer presents a complete solution,
NOTE: Each correct answer is worth one point.
  1. A
    user-defined aggregations
  2. B
    automatic aggregation
  3. C
    query caching
  4. D
    OneLake integration

Correct Answer:
BD
chatbot-img GPT-4o - Answer
The correct answers, Automatic Aggregation and OneLake integration, synergistically reduce query execution time for large datasets in DirectQuery mode. Automatic Aggregation leverages machine learning to optimize data retrieval based on usage patterns, whilst OneLake integration reduces the load by managing dataset federations effectively. Both features ensure that your Visuals render faster by intelligently managing how data queries are executed and processed. These integrations facilitate quicker insights, enhancing the user experience by speeding up data interaction in complex reports.

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