Microsoft · Free Practice Questions · Last reviewed May 2026
7real exam-style questions organised by domain, each with the correct answer highlighted and a plain-English explanation of why it's right — and why the others are wrong.
You are monitoring a semantic model in Microsoft Fabric that is experiencing performance degradation. You suspect that the storage engine is struggling with high-cardinality columns during Direct Lake queries. Which Dynamic Management View (DMV) should you query to identify the memory usage of specific columns in the model?
SELECT * FROM $System.DISCOVER_SESSION_STATISTICS
SELECT * FROM $System.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS
This DMV provides detailed information about the segments of data stored for each column, including their size and compression characteristics. It is the primary tool for diagnosing memory pressure issues in the VertiPaq engine. Analyzing this data allows engineers to identify high-cardinality columns that should be optimized or removed to improve performance.
SELECT * FROM $System.MDSCHEMA_MEASURES
SELECT * FROM $System.DISCOVER_CALC_DEPENDENCY
You are configuring a deployment pipeline in Microsoft Fabric to manage the lifecycle of a Lakehouse and several related reports. Which TWO actions can you perform using deployment pipelines to ensure consistency across environments?
Apply deployment rules to change the data source connection of a semantic model.
Deployment rules allow you to automatically update parameters or connection strings as items move between stages. This ensures that the test environment queries the test database while the production environment queries the production database. Without this feature, developers would have to manually update connections, which is a major source of production errors.
Automatically convert a Power BI report into a Paginated report during the deployment.
Restore a deleted workspace by reverting to a previous pipeline deployment stage.
Compare the items in the source and target stages to identify differences before deploying.
The comparison tool within deployment pipelines provides a visual representation of which items are new, modified, or identical across stages. This allows engineers to verify exactly what changes will be applied before committing the deployment. It is a critical maintenance step for preventing the accidental deployment of unfinished or unwanted modifications.
Encrypt individual columns in a Lakehouse table using a custom key during the sync.
Refer to the exhibit. You are reviewing the Git configuration for a Microsoft Fabric workspace. A developer reports that they cannot see their latest changes in the 'dev' branch within the workspace. Based on the exhibit, what is the most likely cause of this issue?
The workspace is connected to a repository that does not exist in the ContosoCorp organization.
The developer has committed changes to the repository but the workspace has not been updated.
In Fabric Git integration, synchronization is not always automatic in both directions for every change. Even if the status is 'Synced', a user may need to click 'Update all' in the source control panel to pull the latest commits from the remote branch into the workspace. This manual step ensures developers control when their workspace environment changes.
The 'directoryName' in the JSON configuration is incorrect and should be the root directory.
The workspace is currently in a 'Read-only' state because it is connected to a Git branch.
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?
The Capacity Metrics app to check for active user sessions on the Lakehouse.
The SQL analytics endpoint to query the system metadata tables for dependencies.
The 'Monitor' hub to view the history of data refresh operations for all items.
The Lineage view in the workspace to perform an impact analysis on the Lakehouse.
Lineage view provides a graphical representation of the relationships between all items in a workspace and across workspaces. By selecting the Lakehouse and viewing its impact analysis, you can see every downstream semantic model and report. This is the standard method in Fabric for identifying dependencies before performing maintenance or updates.
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?
Convert all calculated columns in the semantic model to Power Query M columns.
Run the OPTIMIZE command on the underlying Delta tables in the Lakehouse.
The OPTIMIZE command performs file compaction (bin-packing) on Delta tables, which reduces the number of small files and improves read performance. Since Direct Lake reads Parquet files from the Lakehouse, having optimized, appropriately sized files is essential for fast memory loading and efficient query execution within the semantic model's engine.
Set the 'Direct Lake behavior' property to 'Direct Lake only' to prevent fallback.
By default, Direct Lake models may fall back to DirectQuery mode if the query cannot be satisfied in memory, which significantly slows down performance. Setting the behavior to 'Direct Lake only' helps in identifying performance bottlenecks during development by forcing an error if the model cannot stay in memory, allowing for targeted optimization.
Increase the 'Max Intermediate Rows' setting in the Power BI capacity settings.
Ensure that the Delta tables use V-Order to improve the reading speed of Parquet files.
V-Order is a Microsoft Fabric-specific optimization for Parquet files that reorganizes data to enable faster reading by the Power BI engine. When Delta tables are V-Ordered, the Direct Lake mode can load data into memory much more efficiently. This is a critical maintenance step for any high-performance Direct Lake implementation in Fabric.
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?
Assign individual user permissions to each item within the workspace for granular control.
Use Microsoft Entra ID (formerly Azure AD) groups for workspace role assignments.
Using security groups allows administrators to manage access at scale. When a user's role changes, updating their group membership automatically updates their access across all relevant Fabric workspaces. This practice ensures consistency, simplifies auditing, and aligns with enterprise identity management standards, making it much easier to maintain a secure environment over time.
Create a separate capacity for every workspace to isolate resource consumption.
Disable the 'Tenant settings' for all users except for one global administrator.
Implement a workspace naming convention that includes the department and environment.
A standardized naming convention (e.g., 'FIN-PROD-Reporting') is a simple yet powerful maintenance tool. It allows users and administrators to quickly identify the purpose, owner, and lifecycle stage of a workspace. This clarity reduces confusion, helps in organizing the Fabric tenant, and makes it much easier to apply automated scripts for monitoring or cleanup tasks.
Want more Maintain a Data Analytics Solution practice?
Practice this domainYou are designing a data ingestion strategy from an on-premises SQL Server to a Microsoft Fabric Lakehouse. You want to utilize the 'Fast Copy' feature in Dataflows Gen2 to maximize throughput. Which TWO conditions must be met to enable this capability? (Select TWO)
The 'Enable staging' option must be selected for the dataflow.
Fast Copy relies on the Fabric Data Factory orchestration engine to move data directly. This process requires staging to be enabled, allowing the system to land data in a temporary storage area before final delivery, which facilitates the high-speed transfer bypass of the standard Mashup engine.
The dataflow must use a Fabric Notebook as a destination.
The transformation steps must only include supported connectors and basic operations.
Fast Copy only activates when the transformations are simple enough to be translated into the underlying copy engine's capabilities. If complex M-code functions or transformations are added that require the Power Query Mashup engine, the system will fall back to the slower, standard processing path for ingestion.
A Premium Capacity (P1 or higher) must be assigned to the workspace.
The source SQL Server must have the 'V-Order' property enabled.
Want more Prepare Data practice?
Practice this domainThe DP-600 exam has 60–90 questions and must be completed in 120 minutes. The passing score is 700/1000.
Scenario-based questions covering exam objectives with detailed answer explanations.
The exam covers 2 domains: Maintain a Data Analytics Solution, Prepare Data. Questions are weighted by domain — higher-weight domains appear more on your actual exam.
No. These are original exam-style practice questions written against the official Microsoft DP-600 exam objectives. They are not copied from the real exam. Courseiva focuses on genuine understanding, not memorisation of braindumps.
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