DP-600 Practice Test 2 — 10 Questions

Question 1

You are maintaining a data analytics solution that requires Row-Level Security (RLS) on a semantic model. You need to ensure that the RLS rules continue to function correctly even when the model is switched to Direct Lake mode. What is a key requirement for maintaining RLS in this scenario?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The RLS roles must be defined in the semantic model using DAX filter expressions.. Maintaining security in Direct Lake mode requires careful consideration of how RLS is applied. Because Direct Lake bypasses the SQL endpoint and reads Parquet files directly, RLS must be defined within the semantic model itself. Understanding these requirements ensures that sensitive data remains protected regardless of the storage mode or the performance optimizations being applied to the data solution.

Answer

RLS must be configured at the Lakehouse level using SQL Views instead of in the model.

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Single Sign-On (SSO) must be disabled for the Lakehouse connection to support RLS.

Answer

The semantic model must be moved to a Pro capacity to support Direct Lake RLS.

Question 2

You are managing a Microsoft Fabric workspace integrated with Azure DevOps. You have several developers working on the same Lakehouse and Semantic Model. Which TWO actions are required to successfully resolve a merge conflict when synchronizing changes from the remote repository to the workspace?

Accepted Answer

Resolve the conflict in the Azure DevOps repository or a local Git client.. Git integration in Microsoft Fabric necessitates a clear strategy for handling conflicts that arise when multiple developers modify the same items. When the workspace and the remote branch diverge, the system cannot automatically reconcile the differences. Engineers must use external tools and specific Fabric sync commands to ensure the workspace reflects the desired state without losing critical work.

Answer

Delete the conflicting items from the workspace and re-import them.

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Use the 'Undo changes' command in the Source Control side pane.

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Change the workspace connection to a new empty branch.

Question 3

You are using the Tabular Model Definition Language (TMDL) to maintain a complex semantic model in Microsoft Fabric. You need to make a bulk change to the descriptions of 50 different measures. What is the most efficient way to perform this maintenance task?

Accepted Answer

Edit the individual .tmdl files in a code editor and sync the changes via Git.. TMDL is a human-readable format for defining semantic models, making it ideal for bulk maintenance and version control. By editing TMDL files in a text editor or using scripts, engineers can apply changes much faster than using a GUI. This approach is highly recommended for large-scale models where manual updates are time-consuming and prone to inconsistencies across different measures.

Answer

Manually update each description in the Power BI Desktop 'Model View' properties pane.

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Use a Power Automate flow to iterate through the measures and update them via the UI.

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Delete the measures and recreate them using a SQL script in the Lakehouse endpoint.

Question 4

You plan to change the data type of a column in a gold-layer Lakehouse table. You need to use the 'Impact Analysis' feature to identify the potential consequences. Which THREE types of downstream items will be identified by this feature?

Accepted Answer

Semantic models. Impact Analysis is a critical governance tool for maintaining data integrity across a Fabric tenant. It allows engineers to see how changes to a data source propagate through the environment. By identifying affected items before making changes, you can proactively notify stakeholders and update dependent logic, preventing broken reports and ensuring a reliable user experience.

Answer

Data Pipelines

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Gateway connections

Question 5

You plan to rename a column in a gold-layer table within a Fabric Lakehouse. Which THREE actions should you perform to assess and mitigate the impact on the existing analytics solution? (Select THREE)

Accepted Answer

Open the Lineage view to identify downstream semantic models and reports that use the table.. Impact analysis and lineage views are critical for maintaining data integrity when underlying schemas change. Before modifying a column name in a Lakehouse table, an engineer should use these tools to identify downstream dependencies. This proactive approach prevents broken reports, failed data pipelines, and ensures that all stakeholders are notified of upcoming breaking changes in the data architecture.

Answer

Delete the Lakehouse and recreate it with the new schema to ensure all metadata is refreshed.

Answer

Change the workspace name to include 'DEPRECATED' until the column rename is completed.

Question 6

You are maintaining a Fabric workspace and need to grant a colleague the ability to commit changes to the Git repository but prevent them from deleting the workspace itself. Which workspace role should you assign?

Accepted Answer

Contributor. Role-based access control (RBAC) is fundamental to maintaining a secure and functional Fabric environment. Each role provides a different level of authority. For developers who need to interact with Git integration, the role must allow for item modification and synchronization while adhering to the principle of least privilege to protect the workspace infrastructure.

Answer

Viewer

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Admin

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Member

Question 7

Refer to the exhibit. You are reviewing an organization's Fabric security policy. Based on the provided JSON snippet, what is the impact of this policy on your data analytics solution?

Accepted Answer

The policy prevents users from exporting data from all reports within the workspace.. This policy implements a governance guardrail that prevents users from exporting data out of the Fabric workspace. In an enterprise environment, this is crucial for maintaining compliance and preventing data exfiltration. By controlling the export action at the workspace level, you ensure that sensitive insights remain contained within the secure Microsoft Fabric boundary, regardless of user permissions.

Answer

Users can export data from individual reports if they have Owner permissions.

Answer

The policy allows exporting if the data is anonymized.

Answer

The policy only affects users with the Guest role.

Question 8

Refer to the exhibit. A notebook in your Fabric workspace is failing with the provided error. What is the most likely cause?

Accepted Answer

The notebook identity lacks read access to the OneLake item.. The '403 Forbidden' error indicates that the service principal or user identity running the notebook does not have authorization to perform read operations on the specific OneLake path. This is a common permission management issue in Fabric. Ensuring the correct identity has the 'Reader' or higher role on the workspace/item is vital for successful data integration and processing tasks within your notebooks.

Answer

The file does not exist in the specified path.

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The capacity SKU is out of memory.

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The notebook syntax is incorrect.

Question 9

You manage a Microsoft Fabric workspace containing a Lakehouse and several semantic models. You need to implement a data lineage solution that traces data transformations from the original source files ingested into the OneLake landing zone down to the Power BI reports consumed by business users. Which Fabric feature should you use to achieve this requirement natively?

Accepted Answer

Open the workspace lineage view to inspect visual relationships and downstream dependencies across all connected items automatically.. Microsoft Fabric provides built-in lineage views that automatically trace dependencies and relationships between data sources, OneLake artifacts, notebooks, and Power BI semantic models. This native integration eliminates the need for external tools and ensures governance and impact analysis can be performed seamlessly across the entire analytical lifecycle, which is vital when debugging broken pipelines or planning structural workspace modifications.

Answer

Configure Azure Monitor workbook alerts to capture and map incoming data streaming events from OneLake to downstream reports.

Answer

Deploy custom Python scripts inside a Fabric notebook to extract workspace metadata using REST APIs and store relationships in an external SQL database.

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Export Power BI Desktop template files (.pbit) and analyze the data source connection strings using XMLA endpoints.

Question 10

You need to monitor the performance of your Fabric SQL endpoint. Which two metrics should you track to ensure long-running queries are identified and optimized?

Accepted Answer

Total query execution time.. Monitoring query duration and resource consumption is essential for maintaining a healthy Fabric environment. By identifying long-running queries, you can pinpoint inefficient T-SQL code or missing indexes. Tracking these metrics enables proactive performance tuning, ensuring that the SQL endpoint remains responsive to users while keeping resource consumption within the allocated capacity limits for the workspace.

Answer

The number of users logged into the workspace.

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The number of files in the OneLake delta table.

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The number of dashboards generated.