DP-600 — Implementing Analytics Solutions Using Microsoft Fabric
Microsoft

Implementing Analytics Solutions Using Microsoft Fabric (DP-600) Practice Questions

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115 questions
June 17, 2026 updated
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Domain coverage

  • Maintain a data analytics solution
  • Prepare data
  • Implement and manage semantic models

Sample Questions (12 of 115 shown)

Q1 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a data pipeline. You need to ensure that the pipeline runs every four hours on Mondays and Fridays. To what should you set Repeat for the schedule?
  1. Daily
  2. By the minute
  3. Weekly
  4. Hourly
✓ Correct Answer: C
To run a pipeline every four hours on specific days (Monday and Friday), you should set the schedule to Weekly. Weekly scheduling allows you to specify which days of the week the pipeline should run and at what intervals throughout those days.
Q2 Maintain a Data Analytics Solution (25-30%)
You have a Fabric workspace that contains a dataflow. You are exploring a new semantic model. From Power Query, you need to view column information like column quality, column profile, and value distribution. Which three Data view options should you select?
  1. Show column value distribution
  2. Enable details pane
  3. Enable column profile
  4. Show column quality details
  5. Show column profile in details pane
✓ Correct Answer: B, C, D
To view comprehensive column information in Power Query's Data view, you need to Enable details pane (B) to show the details panel, Enable column profile (C) to activate profiling, and Show column quality details (D) to display quality metrics. Column value distribution and profile in details are additional options but the core set is B, C, D.
Q3 Maintain a Data Analytics Solution (25-30%)
You have a Fabric workspace named Workspace1 that contains a dataflow named Dataflow1. Dataflow1 returns 500 rows of data. You need to identify the min and max values for each column in the query results. Which three Data view options should you select?
  1. Show column value distribution
  2. Enable column profile
  3. Show column profile in details pane
  4. Show column quality details
  5. Enable details pane
✓ Correct Answer: A, B, C
To identify min and max values for each column, you need Show column value distribution (A) to see value distribution charts with min/max, Enable column profile (B) to activate profiling, and Show column profile in details pane (C) to view detailed column statistics including min/max values.
Q4 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant. You need to configure OneLake security for users following the principle of least privilege. You have different users who need ReadData permission or ReadAll permission. Which permission should you assign to each user?
  1. ReadAll for users who need to read data via SQL endpoints, ReadData for users who need to read via Lakehouse explorer
  2. ReadData for all users
  3. ReadAll for all users
  4. Admin for users who need read access
✓ Correct Answer: A
In OneLake security, ReadAll permission allows reading data through SQL analytics endpoints and T-SQL, while ReadData permission allows reading data through Lakehouse explorer. Following least privilege, users needing SQL endpoint access get ReadAll, and users needing Lakehouse explorer access get ReadData.
Q5 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a lakehouse named lakehouse1. You need to prevent new tables added to Lakehouse1 from being added automatically to the default semantic model of the lakehouse. What should you configure?
  1. The semantic model settings
  2. The Lakehouse1 settings
  3. The workspace settings
  4. The SQL analytics endpoint settings
✓ Correct Answer: A
In the semantic model settings, you can configure whether new tables in the lakehouse are automatically included in the default semantic model. Disabling this option prevents auto-inclusion while still allowing manual selection of tables for the semantic model.
Q6 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer. When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table. You need to identify whether maintenance tasks were performed on Customer. You run: DESCRIBE HISTORY customer. Does this meet the goal?
  1. Yes
  2. No
✓ Correct Answer: A
DESCRIBE HISTORY customer returns the transaction history of the Delta table, including operations like OPTIMIZE, VACUUM, and other maintenance tasks. By reviewing the history, you can determine whether and when maintenance operations were performed on the table.
Q7 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a Delta table named Customer. When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table. You need to identify whether maintenance tasks were performed on Customer. You run: REFRESH TABLE customer. Does this meet the goal?
  1. Yes
  2. No
✓ Correct Answer: B
REFRESH TABLE is used to refresh the Spark catalog metadata for a table, not to check maintenance history. It does not show whether OPTIMIZE, VACUUM, or other maintenance tasks were performed. To check maintenance history, use DESCRIBE HISTORY customer instead.
Q8 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant. You are creating an Azure Data Factory pipeline. You have a stored procedure that returns the current month's active customer count and their average sales. You need to add an activity that will execute the stored procedure in the warehouse. The return values must be available to downstream activities in the pipeline. Which type of activity should you add?
  1. Switch
  2. Copy data
  3. Append variable
  4. Lookup
✓ Correct Answer: D
The Lookup activity in Azure Data Factory can execute a stored procedure in a warehouse and return the results. The output of the Lookup activity is available to downstream activities, allowing the pipeline to use the stored procedure's return values in subsequent operations.
Q9 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant. You need to implement workspace-level security. A workspace contains lakehouses, warehouses, and semantic models that must be accessible by different security groups. Which approach follows least privilege?
  1. Assign all users to the Admin role on the workspace.
  2. Assign specific security groups to specific item-level permissions.
  3. Assign all users to the Member role and control access at the item level.
  4. Create separate workspaces for each security group.
✓ Correct Answer: B
Following least privilege, you should assign specific security groups to specific item-level permissions rather than granting broad workspace-level access. This ensures that users have only the permissions they need for the specific items (lakehouses, warehouses, semantic models) they require.
Q10 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains an unpartitioned table named Table1. You plan to copy data to Table1 and partition the table based on a date column in the source data. You create a Copy activity to copy the data to Table1. What should you do first to specify the partition column in Destination settings?
  1. From the Destination tab, set Mode to Append.
  2. From the Destination tab, select the partition column.
  3. From the Source tab, select Enable partition discovery.
  4. From the Destination tab, set Mode to Overwrite.
✓ Correct Answer: D
To specify partition columns in the Destination settings of a Copy activity, you must first set Mode to Overwrite. When mode is set to Overwrite, the Destination tab allows you to specify partition columns from the source data. Append mode does not support partitioning.
Q11 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant. You need to configure version control for a workspace. The solution must support branching for semantic models and reports. What should you configure?
  1. OneDrive integration
  2. GitHub integration with the workspace
  3. Azure Repos integration with the workspace
  4. Git integration in the workspace settings
✓ Correct Answer: D
Fabric workspace Git integration supports branching for semantic models and reports. You can connect your workspace to a Git repository (Azure Repos or GitHub) using the workspace settings. Once connected, you can use branches for version control, collaboration, and deployment management.
Q12 Maintain a Data Analytics Solution (25-30%)
You have a Fabric tenant that contains a semantic model named Model1. You publish Model1 to a Fabric workspace. You need to ensure that downstream reports are notified when Model1 changes. What should you configure?
  1. A deployment pipeline
  2. An impact analysis report
  3. A notification alert in the semantic model settings
  4. A subscription in the semantic model settings
✓ Correct Answer: B
Impact analysis in Fabric allows you to identify downstream dependencies from semantic models, including reports and dashboards. By running impact analysis, you can see which items depend on Model1 and notify the relevant users when changes occur.

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Frequently Asked Questions

The most challenging technical hurdle is managing the nuances of Direct Lake storage mode — specifically understanding what causes automatic fallback behaviors to DirectQuery or Import modes and how to optimize memory management inside OneLake to prevent it. Candidates also frequently struggle with multi-engine selection criteria — knowing exactly when to use a Lakehouse vs. a Data Warehouse vs. an Eventhouse based on incoming stream speed and transformation complexity — and writing correct KQL syntax for real-time telemetry analytics. Our practice questions reproduce these exact failure scenarios with step-by-step Direct Lake configuration walkthroughs and KQL query pattern demonstrations.

The definitive learning path consists of the five linked modules under the official Course DP-600T00-A on Microsoft Learn. This is heavily augmented by the Exam Readiness Zone video series for DP-600, which breaks down specific test-taking strategies domain-by-domain, and the official, free DP-600 Practice Assessment tool on Microsoft Learn to evaluate real-time scoring gaps before exam day. Our practice tests complement these resources by providing scenario-based questions that mirror the real exam's multi-engine query format.

The Microsoft Certified: Fabric Analytics Engineer Associate certification is valid for exactly one year from the date achieved. To extend its validity for another year without incurring cost, candidates must successfully pass a free, unproctored online renewal assessment on Microsoft Learn during the 6-month window prior to the certificate's expiration date.

If you do not pass the DP-600 exam on your initial attempt, a strict 24-hour waiting period is required before rescheduling. For any subsequent unsuccessful attempts, a 14-day cooling-off period is enforced between retakes. Candidates are permitted a maximum of five total exam attempts within any rolling 12-month window. Each attempt requires the standard $165 USD exam fee unless protected by an Exam Replay voucher.

The mock exam includes scenario-based questions where you must determine the correct Fabric storage item based on data characteristics — for example, selecting Eventhouse for real-time telemetry streams with KQL queries, Lakehouse for Delta-parquet formatted data with PySpark transformations, or Data Warehouse for structured relational data with SQL query patterns. Direct Lake questions test your understanding of automatic fallback triggers (column-level security enabled on a Direct Lake table, insufficient memory for large model, unsupported DAX functions), optimal fallback resolution strategies, and incremental refresh scheduling to maintain Direct Lake eligibility. Polyglot query exercises require you to read and complete SQL, KQL, DAX, and PySpark code snippets — reproducing the multi-engine format used in the real exam. Every practice question includes a detailed walkthrough of the engine-specific syntax and Fabric architecture decisions.

Yes, our complete DP-600 practice test is available as a downloadable PDF package that includes all scenario-based questions, multi-engine query exercises, case studies, and detailed answer explanations. The PDF covers every domain: Maintain a Data Analytics Solution (Git integration, deployment pipelines, RLS/CLS/OLS, sensitivity labels, Fabric monitoring), Prepare Data (OneLake catalog, Lakehouse vs. Data Warehouse vs. Eventhouse selection, OneLake shortcuts, star schema transformation, SQL/KQL/DAX/PySpark queries), and Implement and Manage Semantic Models (Direct Lake architecture, composite models, calculation groups, DAX optimization, incremental refresh). Download the PDF for offline review during commutes or in restricted network environments.

DP-900 (Azure Data Fundamentals) covers data concepts at a conceptual level only — knowing the difference between structured, semi-structured, and unstructured data, basic relational vs. non-relational storage, and high-level Azure data service descriptions. PL-300 (Power BI Data Analyst) focuses specifically on Power BI report creation, dashboard design, and DAX measures within the traditional Power BI ecosystem. DP-300 (Azure Database Administrator) focuses on Azure SQL administration with T-SQL. DP-600 is the only Microsoft certification that tests the full Fabric analytics stack — from data ingestion through OneLake and Real-Time Hub, multi-engine transformation using SQL/KQL/DAX/PySpark, Direct Lake semantic model architecture, deployment pipelines with Git integration, and workspace governance with column-level and object-level security. If your role involves implementing end-to-end analytics solutions using Microsoft Fabric, DP-600 is the certification that validates those specific skills.

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