DP-600 Maintain a Data Analytics Solution Practice Test 3 — 15 Questions

Question 1

You need to perform maintenance on a shared Lakehouse in Microsoft Fabric. Before making schema changes, you want to identify which downstream reports and semantic models will be affected. Which tool should you use?

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

Accepted Answer

The Lineage view in the workspace to perform an impact analysis on the Lakehouse.. Lineage view and impact analysis are essential for maintaining data integrity in a complex Fabric ecosystem. They provide a visual map of dependencies, allowing engineers to understand the consequences of their changes. This proactive approach prevents breaking downstream assets and helps in communicating maintenance windows to the appropriate stakeholders who rely on the affected data.

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The Capacity Metrics app to check for active user sessions on the Lakehouse.

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The SQL analytics endpoint to query the system metadata tables for dependencies.

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The 'Monitor' hub to view the history of data refresh operations for all items.

Question 2

A large semantic model using Direct Lake mode is experiencing slow query performance. You want to optimize the model's maintenance and performance. Which THREE actions should you take?

Accepted Answer

Run the OPTIMIZE command on the underlying Delta tables in the Lakehouse.. Optimizing Direct Lake models requires a combination of data engineering and model configuration. Direct Lake relies on the ability to load Parquet files directly into memory, so the physical layout of the files and the complexity of the DAX measures are critical factors. Maintaining these aspects ensures that the model can stay in 'Direct Lake' mode without falling back to 'DirectQuery'.

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Convert all calculated columns in the semantic model to Power Query M columns.

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Increase the 'Max Intermediate Rows' setting in the Power BI capacity settings.

Question 3

Your organization is scaling its Microsoft Fabric implementation. You need to establish a maintenance plan for workspace administration. Which TWO practices should you implement to manage workspace security and lifecycle effectively?

Accepted Answer

Use Microsoft Entra ID (formerly Azure AD) groups for workspace role assignments.. Effective workspace maintenance involves balancing developer productivity with security and governance. Using security groups rather than individual users simplifies access management and reduces the risk of orphaned permissions. Implementing a clear workspace naming and ownership policy ensures that the environment remains organized and that responsibility for each asset is clearly defined as the organization grows.

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Assign individual user permissions to each item within the workspace for granular control.

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Create a separate capacity for every workspace to isolate resource consumption.

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Disable the 'Tenant settings' for all users except for one global administrator.

Question 4

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?

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.

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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.

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

Question 5

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.

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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 6

A Lakehouse in your Fabric environment has grown significantly over time, and you notice that query performance on the Delta tables is decreasing. You also want to minimize storage costs by removing older versions of data files that are no longer needed for 'Time Travel'. Which maintenance strategy should you implement?

Accepted Answer

Schedule a notebook to run 'OPTIMIZE' followed by 'VACUUM' on the tables.. Regular maintenance of Delta tables is essential for both performance and cost management in Microsoft Fabric. The OPTIMIZE command improves data layout for faster reads, while the VACUUM command removes obsolete files. Together, these operations keep the Lakehouse efficient by ensuring that only necessary, well-structured data is retained and processed during queries, preventing 'file sprawl' in the underlying storage.

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Run a Spark notebook that executes the 'REORG' command on all tables.

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Enable the 'Auto-shrink' property in the Lakehouse settings to manage storage.

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Delete the Lakehouse and recreate it from the original data sources weekly.

Question 7

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.

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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 8

Refer to the exhibit. You receive this JSON response when checking the Git status of a Fabric workspace. What is the most appropriate next step to maintain the integrity of the Semantic Model named 'SalesModel'?

Accepted Answer

Perform a manual merge in the Git provider to consolidate the branch history.. The exhibit indicates a Git synchronization conflict where changes exist in both the workspace and the remote repository. Maintenance of a production-grade solution requires resolving these discrepancies in a controlled environment. Understanding the status codes helps engineers diagnose synchronization failures and apply the correct remediation steps to ensure that the production environment remains stable and version-aligned.

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Commit the local changes using the 'Override Remote' flag in the Fabric API.

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Disconnect the workspace from Git and reconnect it to a fresh repository.

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Restart the Microsoft Fabric capacity to clear the synchronization lock.

Question 9

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.

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Data Pipelines

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Gateway connections

Question 10

You need to update a sensitivity label for a high-priority dataset in a Microsoft Fabric workspace. You want the new label to automatically apply to all reports and dashboards that use this dataset. Which feature should you ensure is enabled?

Accepted Answer

Lineage-based inheritance. Maintaining security at scale in Microsoft Fabric requires automated tools to ensure data protection policies are consistent. Downstream inheritance for sensitivity labels significantly reduces the administrative burden and the risk of human error. This feature ensures that if a dataset is classified as 'Highly Confidential', all derivative works inherit that same level of protection automatically.

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Mandatory labeling policy

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Workspace default labeling

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Service Principal authentication

Question 11

A Microsoft Fabric capacity is frequently experiencing 'Interactive Delay' during peak hours. You need to implement maintenance strategies to mitigate this without increasing the SKU size. Which TWO strategies should you prioritize?

Accepted Answer

Schedule large Warehouse and Lakehouse refreshes during off-peak hours.. Managing capacity performance is essential for maintaining a responsive analytics environment. Interactive delays occur when the capacity is over-utilized, and the system throttles new requests. By optimizing the distribution of background tasks and improving query efficiency, engineers can maximize the utility of their current SKU and ensure that high-priority interactive reports remain performant.

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Enable 'DirectQuery' for all semantic models to reduce memory load.

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Increase the 'Refresh Frequency' of all reports to ensure data freshness.

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Disable the 'Smoothing' feature in the Fabric Admin portal.

Question 12

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.

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Viewer

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Admin

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Member

Question 13

You need to perform a 'Lineage View' audit in Microsoft Fabric. Which TWO types of information are specifically provided by the Lineage View to help you maintain the solution?

Accepted Answer

The source-to-destination path of data across different workspaces.. Lineage View is an essential maintenance tool for understanding the complexity and health of a data solution. It provides a map of how data flows through the system, which is vital for troubleshooting and change management. By visualizing these paths, engineers can identify bottlenecks, redundant processes, and the potential impact of modifications to upstream sources.

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The DAX query plan for the most expensive visuals in a report.

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A list of individual users who have viewed a specific report in the last 30 days.

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The physical storage location of the Delta files in OneLake.

Question 14

You are using the Microsoft Fabric deployment pipeline. You have successfully deployed a semantic model from Development to Test. You now realize that you need to change the 'Data Source' rule for the Test stage. What will happen to the existing items in the Test stage if you update the rule?

Accepted Answer

The new rule will only apply the next time you deploy from Development to Test.. Understanding how deployment rules behave is critical for maintaining consistent environments. Rules are applied during the deployment process, not retroactively. Knowing when and how rules take effect helps engineers avoid situations where the environment is in an inconsistent state or where manual intervention is required to fix a botched deployment.

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The items in the Test stage will be updated immediately to reflect the new rule.

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The deployment will fail because rules cannot be changed once an item is deployed.

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The rule change will automatically trigger a refresh of the Semantic Model in Test.

Question 15

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.

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

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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.