DP-600 Implementing Analytics Solutions Using Microsoft Fabric Dumps
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Sample Question 4
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 deviationvalues for all the string and numeric columns.Solution: You use the following PySpark expression:df.show()Does this meet the goal?
A. Yes B. No
Answer: B
Explanation: The df.show() method also does not meet the goal. It is used to show the
contents of the DataFrame, not to compute statistical functions. References = The usage of the show() function is documented in the PySpark API documentation.
Sample Question 5
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1contains a subfolder named Subfolder1 that contains CSV files. You need to convert theCSV files into the delta format that has V-Order optimization enabled. What should you dofrom Lakehouse explorer?
A. Use the Load to Tables feature. B. Create a new shortcut in the Files section. C. Create a new shortcut in the Tables section. D. Use the Optimize feature.
Answer: D
Explanation: To convert CSV files into the delta format with Z-Order optimization enabled,
you should use the Optimize feature (D) from Lakehouse Explorer. This will allow you to
optimize the file organization for the most efficient querying. References = The process for
converting and optimizing file formats within a lakehouse is discussed in the lakehouse
management documentation.
Sample Question 6
You are creating a semantic model in Microsoft Power Bl Desktop.You plan to make bulk changes to the model by using the Tabular Model DefinitionLanguage (TMDL) extension for Microsoft Visual Studio Code.You need to save the semantic model to a file.Which file format should you use?
A. PBIP B. PBIX C. PBIT D. PBIDS
Answer: B
Explanation: When saving a semantic model to a file that can be edited using the Tabular Model Scripting Language (TMSL) extension for Visual Studio Code, the PBIX (Power BI
Desktop) file format is the correct choice. The PBIX format contains the report, data model,
and queries, and is the primary file format for editing in Power BI Desktop. References =
Microsoft's documentation on Power BI file formats and Visual Studio Code provides
further clarification on the usage of PBIX files.
Sample Question 7
You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1.Report1 includes a Python visual. Data displayed by the visual is grouped automaticallyand duplicate rows are NOT displayed. You need all rows to appear in the visual. Whatshould you do?
A. Reference the columns in the Python code by index. B. Modify the Sort Column By property for all columns. C. Add a unique field to each row. D. Modify the Summarize By property for all columns.
Answer: C
Explanation: To ensure all rows appear in the Python visual within a Power BI report,
option C, adding a unique field to each row, is the correct solution. This will prevent
automatic grouping by unique values and allow for all instances of data to be represented
in the visual. References = For more on Power BI Python visuals and how they handle
data, please refer to the Power BI documentation.
Sample Question 8
You have a Fabric tenant tha1 contains a takehouse named Lakehouse1. Lakehouse1contains a Delta table named Customer.When you query Customer, you discover that the query is slow to execute. You suspectthat 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:REFRESH TABLE customerDoes this meet the goal?
A. Yes B. No
Answer: B
Explanation: No, the REFRESH TABLE statement does not provide information on whether maintenance tasks were performed. It only updates the metadata of a table to
reflect any changes on the data files. References = The use and effects of the REFRESH
TABLE command are explained in the Spark SQL documentation.
Sample Question 9
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 deviationvalues for all the string and numeric columns.Solution: You use the following PySpark expression:df.explain()Does this meet the goal?
A. Yes B. No
Answer: B
Explanation: The df.explain() method does not meet the goal of evaluating data to
calculate statistical functions. It is used to display the physical plan that Spark will execute.
References = The correct usage of the explain() function can be found in the PySpark
documentation.
Sample Question 10
You have a Fabric tenant that contains a lakehouse.You plan to query sales data files by using the SQL endpoint. The files will be in anAmazon Simple Storage Service (Amazon S3) storage bucket.You need to recommend which file format to use and where to create a shortcut.Which two actions should you include in the recommendation? Each correct answerpresents part of the solution.NOTE: Each correct answer is worth one point.
A. Create a shortcut in the Files section. B. Use the Parquet format C. Use the CSV format. D. Create a shortcut in the Tables section. E. Use the delta format.
Answer: B,D
Explanation: You should use the Parquet format (B) for the sales data files because it is
optimized for performance with large datasets in analytical processing and create a
shortcut in the Tables section (D) to facilitate SQL queries through the lakehouse's SQL
endpoint. References = The best practices for working with file formats and shortcuts in a
lakehouse environment are covered in the lakehouse and SQL endpoint documentation
provided by the cloud data platform services.
Sample Question 11
You have source data in a folder on a local computer.You need to create a solution that will use Fabric to populate a data store. The solutionmust meet the following requirements:• Support the use of dataflows to load and append data to the data store.• Ensure that Delta tables are V-Order optimized and compacted automatically. Which type of data store should you use?
A. a lakehouse B. an Azure SQL database C. a warehouse D. a KQL database
Answer: A
Explanation: A lakehouse (A) is the type of data store you should use. It supports
dataflows to load and append data and ensures that Delta tables are Z-Order optimized
and compacted automatically. References = The capabilities of a lakehouse and its support
for Delta tables are described in the lakehouse and Delta table documentation.
Sample Question 12
You are analyzing the data in a Fabric notebook.You have a Spark DataFrame assigned to a variable named df.You need to use the Chart view in the notebook to explore the data manually.Which function should you run to make the data available in the Chart view?
A. displayMTML B. show C. write D. display
Answer: D
Explanation: The display function is the correct choice to make the data available in the
Chart view within a Fabric notebook. This function is used to visualize Spark DataFrames
in various formats including charts and graphs directly within the notebook environment.
References = Further explanation of the display function can be found in the official
documentation on Azure Synapse Analytics notebooks.
Sample Question 13
You have a Fabric tenant that contains a warehouse.A user discovers that a report that usually takes two minutes to render has been running for45 minutes and has still not rendered.You need to identify what is preventing the report query from completing.Which dynamic management view (DMV) should you use?
A. sys.dm-exec_requests B. sys.dn_.exec._sessions C. sys.dm._exec._connections D. sys.dm_pdw_exec_requests
Answer: D
Explanation: The correct DMV to identify what is preventing the report query from
completing is sys.dm_pdw_exec_requests (D). This DMV is specific to Microsoft
Analytics Platform System (previously known as SQL Data Warehouse), which is the
environment assumed to be used here. It provides information about all queries and load
commands currently running or that have recently run. References = You can find more
about DMVs in the Microsoft documentation for Analytics Platform System.
Sample Question 14
You are the administrator of a Fabric workspace that contains a lakehouse namedLakehouse1. Lakehouse1 contains the following tables:• Table1: A Delta table created by using a shortcut• Table2: An external table created by using Spark• Table3: A managed tableYou plan to connect to Lakehouse1 by using its SQL endpoint. What will you be able to doafter connecting to Lakehouse1?
A. ReadTable3. B. Update the data Table3. C. ReadTable2. D. Update the data in Table1.
Answer: D
Sample Question 15
You have a Fabric tenant that contains 30 CSV files in OneLake. The files are updateddaily.You create a Microsoft Power Bl semantic model named Modell that uses the CSV files asa data source. You configure incremental refresh for Model 1 and publish the model to aPremium capacity in the Fabric tenant.When you initiate a refresh of Model1, the refresh fails after running out of resources.What is a possible cause of the failure?
A. Query folding is occurring. B. Only refresh complete days is selected. C. XMLA Endpoint is set to Read Only. D. Query folding is NOT occurring. E. The data type of the column used to partition the data has changed.
Answer: D
Explanation: A possible cause for the failure is that query folding is NOT occurring (D).
Query folding helps optimize refresh by pushing down the query logic to the source system,
reducing the amount of data processed and transferred, hence conserving resources.
References = The Power BI documentation on incremental refresh and query folding
provides detailed information on this topic.
Exam Code: DP-600Exam Name: Implementing Analytics Solutions Using Microsoft FabricLast Update: May 20, 2024Questions: 80
