Microsoft Microsoft Certifications DP-600 Questions & Answers

• Question 1:

  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. MaxN

  B. Table.Max

  C. Table.Range

  D. Table.Profile

  Correct Answer: B

  Explanation: The Table.Max function should be used in a Power Query step to identify the maximum values for the numeric columns. This function is designed to calculate the maximum value across each column in a table, which suits the requirement of finding maximum values for numeric columns. References = For detailed information on Power Query functions, including Table.Max, please refer to Power Query M function reference.

• Question 2:

  You have a Fabric tenant that contains a workspace named Workspace^ Workspacel is assigned to a Fabric capacity.

  You need to recommend a solution to provide users with the ability to create and publish custom Direct Lake semantic models by using external tools. The solution must follow the principle of least privilege.

  Which three actions in the Fabric Admin portal should you include in the recommendation? Each correct answer presents part of the solution.

  NOTE: Each correct answer is worth one point.

  A. From the Tenant settings, set Allow XMLA Endpoints and Analyze in Excel with on- premises datasets to Enabled

  B. From the Tenant settings, set Allow Azure Active Directory guest users to access Microsoft Fabric to Enabled

  C. From the Tenant settings, select Users can edit data models in the Power Bl service.

  D. From the Capacity settings, set XMLA Endpoint to Read Write

  E. From the Tenant settings, set Users can create Fabric items to Enabled

  F. From the Tenant settings, enable Publish to Web

  Correct Answer: ACD

  Explanation: For users to create and publish custom Direct Lake semantic models using external tools, following the principle of least privilege, the actions to be included are enabling XMLA Endpoints (A), editing data models in Power BI service (C), and setting XMLA Endpoint to Read-Write in the capacity settings (D). References = More information can be found in the Admin portal of the Power BI service documentation, detailing tenant and capacity settings.

• Question 3:

  You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD).

  Which two actions should you include in the process? Each correct answer presents part of the solution.

  NOTE: Each correct answer is worth one point.

  A. Update rows when the non-key attributes have changed.

  B. Insert new rows when the natural key exists in the dimension table, and the non-key attribute values have changed.

  C. Update the effective end date of rows when the non-key attribute values have changed.

  D. Insert new records when the natural key is a new value in the table.

  Correct Answer: AD

  Explanation: For a Type 1 SCD, you should include actions that update rows when non- key attributes have changed (A), and insert new records when the natural key is a new value in the table (D). A Type 1 SCD does not track historical data, so you always overwrite the old data with the new data for a given key. References = Details on Type 1 slowly changing dimension patterns can be found in data warehousing literature and Microsoft's official documentation.

• Question 4:

  You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.

  You have a Microsoft Power Bl report named Report1 that uses the model. Report! contains visuals on multiple pages.

  You need to reduce the query execution time for the visuals on all the pages.

  What are two features that you can use? Each correct answer presents a complete solution.

  NOTE: Each correct answer is worth one point.

  A. user-defined aggregations

  B. automatic aggregation

  C. query caching

  D. OneLake integration

  Correct Answer: AC

  Explanation: User-defined aggregations (A) and query caching (C) are two features that can help reduce query execution time. User-defined aggregations allow precalculation of large datasets, and query caching stores the results of queries temporarily to speed up future queries. References = Microsoft Power BI documentation on performance optimization offers in-depth knowledge on these features.

• Question 5:

  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.

  You need to specify the partition column in the Destination settings of the Copy activity.

  What should you do first?

  A. From the Destination tab, set Mode to Append.

  B. From the Destination tab, select the partition column,

  C. From the Source tab, select Enable partition discovery

  D. From the Destination tab, set Mode to Overwrite.

  Correct Answer: A

  Explanation: Before specifying the partition column in the Destination settings of the Copy activity, you should set Mode to Append (A). This will allow the Copy activity to add data to the table while taking the partition column into account. References = The configuration options for Copy activities and partitioning in Azure Data Factory, which are applicable to Fabric dataflows, are outlined in the official Azure Data Factory documentation.

• Question 6:

  You have a Fabric workspace named Workspace 1 that contains a dataflow named Dataflow1. Dataflow! has a query that returns 2.000 rows. You view the query in Power Query as shown in the following exhibit.

  

  What can you identify about the pickupLongitude column?

  A. The column has duplicate values.

  B. All the table rows are profiled.

  C. The column has missing values.

  D. There are 935 values that occur only once.

  Correct Answer: A

  Explanation: The pickupLongitude column has duplicate values. This can be inferred because the 'Distinct count' is 935 while the 'Count' is 1000, indicating that there are repeated values within the column. References = Microsoft Power BI documentation on data profiling could provide further insights into understanding and interpreting column statistics like these.

• Question 7:

  You have a Fabric tenant that contains a new semantic model in OneLake.

  You use a Fabric notebook to read the data into a Spark DataFrame.

  You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns.

  Solution: You use the following PySpark expression:

  df .sumary ()

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: A

  Explanation: Yes, the df.summary() method does meet the goal. This method is used to compute specified statistics for numeric and string columns. By default, it provides statistics such as count, mean, stddev, min, and max. References = The PySpark API documentation details the summary() function and the statistics it provides.

• Question 8:

  You have a Fabric tenant that contains a semantic model. The model uses Direct Lake mode.

  You suspect that some DAX queries load unnecessary columns into memory.

  You need to identify the frequently used columns that are loaded into memory.

  What are two ways to achieve the goal? Each correct answer presents a complete solution.

  NOTE: Each correct answer is worth one point.

  A. Use the Analyze in Excel feature.

  B. Use the Vertipaq Analyzer tool.

  C. Query the $system.discovered_STORAGE_TABLE_COLUMN-iN_SEGMeNTS dynamic management view (DMV).

  D. Query the discover_hehory6Rant dynamic management view (DMV).

  Correct Answer: BC

  Explanation: The Vertipaq Analyzer tool (B) and querying the $system.discovered_STORAGE_TABLE_COLUMNS_IN_SEGMENTS dynamic management view (DMV) (C) can help identify which columns are frequently loaded into memory. Both methods provide insights into the storage and retrieval aspects of the semantic model. References = The Power BI documentation on Vertipaq Analyzer and DMV queries offers detailed guidance on how to use these tools for performance analysis.

• Question 9:

  You have a Fabric tenant that contains a warehouse. The warehouse uses row-level security (RLS). You create a Direct Lake semantic model that uses the Delta tables and RLS of the warehouse. When users interact with a report built from the model, which mode will be used by the DAX queries?

  A. DirectQuery

  B. Dual

  C. Direct Lake

  D. Import

  Correct Answer: A

  Explanation: When users interact with a report built from a Direct Lake semantic model that uses row-level security (RLS), the DAX queries will operate in DirectQuery mode (A). This is because the model directly queries the underlying data source without importing data into Power BI. References = The Power BI documentation on DirectQuery provides detailed explanations of how RLS and DAX queries function in this mode.

• Question 10:

  You have a Fabric tenant tha1 contains a takehouse 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.

  Solution: You run the following Spark SQL statement:

  EXPLAIN TABLE customer

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: B

  Explanation: No, the EXPLAIN TABLE statement does not identify whether maintenance tasks were performed on a table. It shows the execution plan for a query. References = The usage and output of the EXPLAIN command can be found in the Spark SQL documentation.