This is the free Microsoft DP-600 practice question bank —
100 of 189 total questions, each with a full explanation, free to
read with no signup required. Updated 2026-04-24.
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Question 1
DRAG DROP
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You have a Fabric lakehouse named Lakehouse1.
You have the data sources shown in the following table.
You need to ingest data from both data sources into Lakehouse1. The solution must minimize maintenance and development time.
What should you use to ingest the data into each data source? To answer, drag the appropriate options to the correct data sources. Each option may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Show Answer
Correct Answer: Datasource1:
A Dataflow Gen2
Datasource2:
An eventstream
Explanation: Datasource1 uses Azure SQL Managed Instance with CDC and large daily loads; Dataflow Gen2 natively supports CDC ingestion into Fabric Lakehouse with minimal development and maintenance.
Datasource2 is streaming data already arriving in Azure Event Hubs, which is best ingested into Fabric using an Eventstream designed for real-time streaming scenarios.
Question 2
You have a Fabric tenant that contains a warehouse.
You use a dataflow to load a new dataset from OneLake to the warehouse.
You need to add a Power Query step to identify the maximum values for the numeric columns.
Which function should you include in the step?
A. Table.Range
B. Table.MaxN
C. Table.Profile
Show Answer
Correct Answer: C
Explanation: In Power Query, the Table.Profile function generates column-level profiling information for a table, including minimum and maximum values for numeric columns. This makes it the appropriate function to identify maximum values across numeric columns in a dataflow step.
Question 3
You have a Fabric tenant that contains a workspace named Workspace1 and a user named User1. Workspace1 contains a warehouse named DW1.
You share DW1 with User1 and assign User1 the default permissions for DW1.
What can User1 do?
A. Read data from the tables in DW1.
B. Build reports by using the default dataset.
C. Read the underlying Parquet files from OneLake.
D. Connect to DW1 via the TDS (Tabular Data Stream) endpoint.
Show Answer
Correct Answer: A
Explanation: When a Fabric warehouse is shared with default permissions, the recipient gets Read access. This allows them to query and read data from tables and views in the warehouse via the SQL analytics endpoint. It does not grant file-level OneLake access or additional build/authoring permissions, and the question focuses on the practical outcome of the default permission: reading table data.
Question 4
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2.
Workspace1 is used as the development environment. Workspace2 is used as the production environment. Each environment uses a different storage account.
Workspace1 contains a Dataflow Gen2 named Dataflow1. The data source of Dataflow1 is a CSV file in blob storage.
You plan to implement a deployment pipeline to deploy items from Workspace1 to Workspace2.
You need to ensure that the data source references the correct location in the production environment.
What should you do?
A. Create a data source rule only.
B. Create a parameter rule only.
C. Create a data source rule and a parameter rule.
D. After implementing the deployment pipeline, manually change the data source
Show Answer
Correct Answer: A
Explanation: A Dataflow Gen2 connection to blob storage is handled through a data source (connection). In a deployment pipeline, a data source rule remaps the development storage account connection to the production storage account automatically. A parameter rule is only required if you explicitly parameterized values such as folder or file paths inside the dataflow, which is not stated here. Therefore, a data source rule alone is sufficient.
Question 5
HOTSPOT
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You have a Fabric workspace named Workspace1 that uses the Premium Per User (PPU) license mode and contains a semantic model named Model1.
Large semantic model storage format is selected for Model1.
You need to ensure that tables imported into Model1 are written automatically to Delta tables in OneLake.
What should you do for Model1 and Workspace1? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Show Answer
Correct Answer: Model1:
Enable OneLake integration.
Workspace1:
Change the license mode to Fabric capacity.
Explanation: Automatic writing of imported tables to Delta tables in OneLake requires OneLake integration at the semantic model level and a Fabric capacity–backed workspace. PPU workspaces don’t support this behavior, so the workspace must be moved to Fabric capacity.
Question 6
You have a Microsoft Power BI semantic model.
You need to identify any surrogate key columns in the model that have the Summarize By property set to a value other than to None. The solution must minimize effort.
What should you use?
A. Performance Analyzer in Power BI Desktop
B. Model explorer in Microsoft Power BI Desktop
C. Model view in Microsoft Power BI Desktop
D. DAX Formatter in DAX Studio
Show Answer
Correct Answer: B
Explanation: The Model explorer in Power BI Desktop lists all tables and columns with their properties, including Summarize By. It allows you to quickly scan or filter columns to identify surrogate keys that are not set to Summarize By = None, which requires less effort than inspecting each column individually in Model view. The other options do not directly expose this property in a convenient way.
Question 7
DRAG DROP
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You have a Fabric eventhouse named Eventhouse1 that contains a table named Weatherdata. A sample of the data in Weatherdata is shown in the following table.
You plan to use a KQL queryset to manipulate the data in Eventhouse1. The result set must have the following columns.
You need to build the query.
Which four KQL statements should you use in sequence? To answer, move the appropriate statements from the list of statements to the answer area and arrange them in the correct order.
Show Answer
Correct Answer: Weatherdata
| sort by Datetime asc
| extend Delta_temperature = Temperature - prev(Temperature)
| summarize Delta_temperature = sum(Temperature) - sum(prev(Temperature)) by Datetime
Explanation: Start from the Weatherdata table, sort by Datetime so row order is correct, calculate the temperature difference from the preceding row using prev(), and then shape the final result with a summarize step as required by the available statements.
Question 8
You have a Fabric workspace named Workspace1 that contains an eventstream named Eventstream1.
Eventstream1 reads data from an Azure event hub named Eventhub1.
Eventhub1 contains the following columns.
You need to add a continuous percentile calculation to the Payload column. The solution must minimize development effort.
What should you do?
A. Add a KQL queryset to Workspace1.
B. Add a Group by transformation to Eventstream1.
C. Add a Manage fields transformation to Eventstream1.
D. Add an Aggregate transformation to Eventstream1.
Show Answer
Correct Answer: D
Explanation: A continuous percentile calculation on streaming data is a built-in statistical aggregation. In Microsoft Fabric Eventstreams, the Aggregate transformation natively supports percentile functions and operates continuously on incoming events with minimal configuration. This avoids writing custom queries or code and keeps the logic inside the eventstream, minimizing development effort. The other transformations (Group by, Manage fields) do not compute percentiles, and a KQL queryset requires additional development and maintenance outside the eventstream.
Question 9
You have a semantic model named Model1 that contains data that relates to customers and their bank account balances.
Model1 has the following tables and columns.
A customer can have one or more accounts. Each account can be associated to multiple customers.
You need to ensure that users can query Model1 to identify the total transaction amounts by customer.
What should you add to Model1?
A. a many-to-many relationship between FactTransaction and Dim Customer
B. a bridge table with relationships to DimCustomer and DimAccount
C. a bridge table with relationships to FactTransaction and DimCustomer
D. the CustomerKey column in FactTransaction and a relationship to DimCustomer
Show Answer
Correct Answer: B
Explanation: Customers and accounts have a many-to-many relationship, while transactions relate to accounts. To correctly aggregate transaction amounts by customer, the many-to-many relationship between DimCustomer and DimAccount must be resolved. Adding a bridge (mapping) table between DimCustomer and DimAccount allows FactTransaction to relate to DimAccount and then filter correctly to customers through the bridge, ensuring accurate totals.
Question 10
HOTSPOT
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You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData that stores the following data.
You need to create a column named FirstPickupDateTime that will contain the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Show Answer
Correct Answer: row_window_session
!=
Explanation: row_window_session() creates hourly sessions and resets when the payment_type changes. Using the != prev(payment_type) condition starts a new window per payment type, returning the first datetime of each 1-hour window.
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