DP-600 Certification Overview - [Dec 18, 2024] Latest DP-600 PDF Dumps
The Best Microsoft DP-600 Study Guides and Dumps of 2024
Microsoft DP-600 Exam Syllabus Topics:
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NEW QUESTION # 18
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. OneLake integration
- B. user-defined aggregations
- C. query caching
- D. automatic aggregation
Answer: A,C
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.
NEW QUESTION # 19
You to need assign permissions for the data store in the AnalyticsPOC workspace. The solution must meet the security requirements.
Which additional permissions should you assign when you share the data store? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* Data Engineers: Read All SQL analytics endpoint data
* Data Analysts: Read All Apache Spark
* Data Scientists: Read All SQL analytics endpoint data
The permissions for the data store in the AnalyticsPOC workspace should align with the principle of least privilege:
* Data Engineers need read and write access but not to datasets or reports.
* Data Analysts require read access specifically to the dimensional model objects and the ability to create Power BI reports.
* Data Scientists need read access via Spark notebooks. These settings ensure each role has the necessary permissions to fulfill their responsibilities without exceeding their required access level.
NEW QUESTION # 20
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. write
- B. show
- C. displayMTML
- 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.
NEW QUESTION # 21
You have a data warehouse that contains a table named Stage. Customers. Stage-Customers contains all the customer record updates from a customer relationship management (CRM) system. There can be multiple updates per customer You need to write a T-SQL query that will return the customer ID, name, postal code, and the last updated time of the most recent row for each customer ID.
How should you complete the code? To answer, select the appropriate options in the answer area, NOTE Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* In the ROW_NUMBER() function, choose OVER (PARTITION BY CustomerID ORDER BY LastUpdated DESC).
* In the WHERE clause, choose WHERE X = 1.
To select the most recent row for each customer ID, you use the ROW_NUMBER() window function partitioned by CustomerID and ordered by LastUpdated in descending order. This will assign a row number of 1 to the most recent update for each customer. By selecting rows where the row number (X) is 1, you get the latest update per customer.
References =
* Use the OVER clause to aggregate data per partition
* Use window functions
NEW QUESTION # 22
You create a semantic model by using Microsoft Power Bl Desktop. The model contains one security role named SalesRegionManager and the following tables:
* Sales
* SalesRegion
* Sales Ad dress
You need to modify the model to ensure that users assigned the SalesRegionManager role cannot see a column named Address in Sales Address.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
To ensure that users assigned the SalesRegionManager role cannot see the Address column in the SalesAddress table, follow these steps in sequence:
* Open the model in Tabular Editor.
* Select the Address column in SalesAddress.
* Set Object Level Security to None for SalesRegionManager.
NEW QUESTION # 23
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 an Amazon 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 answer presents part of the solution.
NOTE: Each correct answer is worth one point.
- A. Create a shortcut in the Tables section.
- B. Create a shortcut in the Files section.
- C. Use the delta format.
- D. Use the CSV format.
- E. Use the Parquet format
Answer: A,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.
NEW QUESTION # 24
You are analyzing customer purchases in a Fabric notebook by using PySpanc You have the following DataFrames:
You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling. You write the following code.
Which code should you run to populate the results DataFrame?
- A.
- B.
- C.
- D.
Answer: D
Explanation:
The correct code to populate the results DataFrame with minimal data shuffling is Option A. Using the broadcast function in PySpark is a way to minimize data movement by broadcasting the smaller DataFrame ( customers) to each node in the cluster. This is ideal when one DataFrame is much smaller than the other, as in this case with customers. References = You can refer to the official Apache Spark documentation for more details on joins and the broadcast hint.
NEW QUESTION # 25
You have a Fabric tenant named Tenant1 that contains a workspace named WS1. WS1 uses a capacity named C1 and contains a dawset named DS1. You need to ensure read-write access to DS1 is available by using the XMLA endpoint. What should be modified first?
- A. the WS1 settings
- B. the Tenant1 settings
- C. the C1 settings
- D. the DS1 settings
Answer: C
NEW QUESTION # 26
You have a Fabric tenant that contains a machine learning model registered in a Fabric workspace. You need to use the model to generate predictions by using the predict function in a fabric notebook. Which two languages can you use to perform model scoring? Each correct answer presents a complete solution. NOTE:
Each correct answer is worth one point.
- A. Spark SQL
- B. DAX EC.
- C. PySpark
- D. T-SQL
Answer: A,C
Explanation:
The two languages you can use to perform model scoring in a Fabric notebook using the predict function are Spark SQL (option C) and PySpark (option D). These are both part of the Apache Spark ecosystem and are supported for machine learning tasks in a Fabric environment. References = You can find more information about model scoring and supported languages in the context of Fabric notebooks in the official documentation on Azure Synapse Analytics.
NEW QUESTION # 27
You have a Fabric tenant that 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:
DESCRIBE HISTORY customer
Does this meet the goal?
- A. No
- B. Yes
Answer: B
NEW QUESTION # 28
You need to design a semantic model for the customer satisfaction report.
Which data source authentication method and mode should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
For the semantic model design required for the customer satisfaction report, the choices for data source authentication method and mode should be made based on security and performance considerations as per the case study provided.
Authentication method: The data should be accessed securely, and given that row-level security (RLS) is required for users executing T-SQL queries, you should use an authentication method that supports RLS.
Service principal authentication is suitable for automated and secure access to the data, especially when the access needs to be controlled programmatically and is not tied to a specific user's credentials.
Mode: The report needs to show data as soon as it is updated in the data store, and it should only contain data from the current and previous year. DirectQuery mode allows for real-time reporting without importing data into the model, thus meeting the need for up-to-date data. It also allows for RLS to be implemented and enforced at the data source level, providing the necessary security measures.
Based on these considerations, the selections should be:
* Authentication method: Service principal authentication
* Mode: DirectQuery
NEW QUESTION # 29
You have a Fabric tenant that contains two lakehouses.
You are building a dataflow that will combine data from the lakehouses. The applied steps from one of the queries in the dataflow is shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 30
You have a Fabric warehouse that contains a table named Staging.Sales. Staging.Sales contains the following columns.
You need to write a T-SQL query that will return data for the year 2023 that displays ProductID and ProductName arxl has a summarized Amount that is higher than 10,000. Which query should you use?
- A.
- B.
- C.
- D.
Answer: C
Explanation:
The correct query to use in order to return data for the year 2023 that displays ProductID, ProductName, and has a summarized Amount greater than 10,000 is Option B. The reason is that it uses the GROUP BY clause to organize the data by ProductID and ProductName and then filters the result using the HAVING clause to only include groups where the sum of Amount is greater than 10,000. Additionally, the DATEPART(YEAR, SaleDate) = '2023' part of the HAVING clause ensures that only records from the year 2023 are included.
References = For more information, please visit the official documentation on T-SQL queries and the GROUP BY clause at T-SQL GROUP BY.
NEW QUESTION # 31
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a subfolder named Subfolder1 that contains CSV files. You need to convert the CSV files into the delta format that has V-Order optimization enabled. What should you do from Lakehouse explorer?
- A. Use the Optimize feature.
- B. Create a new shortcut in the Tables section.
- C. Create a new shortcut in the Files section.
- D. Use the Load to Tables feature.
Answer: A
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.
NEW QUESTION # 32
You are implementing two dimension tables named Customers and Products in a Fabric warehouse.
You need to use slowly changing dimension (SCO) to manage the versioning of data. The solution must meet the requirements shown in the following table.
Which type of SCD should you use for each table? To answer, drag the appropriate SCD types to the correct tables. Each SCD type 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.
Answer:
Explanation:
Explanation:
For the Customers table, where the requirement is to create a new version of the row, you would use:
* Type 2 SCD: This type allows for the creation of a new record each time a change occurs, preserving the history of changes over time.
For the Products table, where the requirement is to overwrite the existing value in the latest row, you would use:
* Type 1 SCD: This type updates the record directly, without preserving historical data.
NEW QUESTION # 33
You need to create a DAX measure to calculate the average overall satisfaction score.
How should you complete the DAX code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* The measure should use the AVERAGE function to calculate the average value.
* It should reference the Response Value column from the 'Survey' table.
* The 'Number of months' should be used to define the period for the average calculation.
To calculate the average overall satisfaction score using DAX, you would need to use the AVERAGE function on the response values related to satisfaction questions. The DATESINPERIOD function will help in calculating the rolling average over the last 12 months.
NEW QUESTION # 34
You are creating a dataflow in Fabric to ingest data from an Azure SQL database by using a T-SQL statement.
You need to ensure that any foldable Power Query transformation steps are processed by the Microsoft SQL Server engine.
How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value 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.
Answer:
Explanation:
Explanation:
You should complete the code as follows:
* Table
* NativeQuery
* EnableFolding
In Power Query, using Table before the SQL statement ensures that the result of the SQL query is treated as a table. NativeQuery allows a native database query to be passed through from Power Query to the source database. The EnableFolding option ensures that any subsequent transformations that can be folded will be sent back and executed at the source database (Microsoft SQL Server engine in this case).
NEW QUESTION # 35
You have a Microsoft Power Bl semantic model that contains measures. The measures use multiple calculate functions and a filter function.
You are evaluating the performance of the measures.
In which use case will replacing the filter function with the keepfilters function reduce execution time?
- A. when the filter function references a measure
- B. when the filter function references columns from multiple tables
- C. when the filter function references a column from a single table that uses Import mode
- D. when the filter function uses a nested calculate function
Answer: D
Explanation:
The KEEPFILTERS function modifies the way filters are applied in calculations done through the CALCULATE function. It can be particularly beneficial to replace the FILTER function with KEEPFILTERS when the filter context is being overridden by nested CALCULATE functions, which may remove filters that are being applied on a column. This can potentially reduce execution time because KEEPFILTERS maintains the existing filter context and allows the nested CALCULATE functions to be evaluated more efficiently.
References: This information is based on the DAX reference and performance optimization guidelines in the Microsoft Power BI documentation.
NEW QUESTION # 36
You are the administrator of a Fabric workspace that contains a lakehouse named Lakehouse1. 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 table
You plan to connect to Lakehouse1 by using its SQL endpoint. What will you be able to do after connecting to Lakehouse1?
- A. ReadTable2.
- B. ReadTable3.
- C. Update the data Table3.
- D. Update the data in Table1.
Answer: D
NEW QUESTION # 37
You have an Azure Repos Git repository named Repo1 and a Fabric-enabled Microsoft Power Bl Premium capacity. The capacity contains two workspaces named Workspace! and Workspace2. Git integration is enabled at the workspace level.
You plan to use Microsoft Power Bl Desktop and Workspace! to make version-controlled changes to a semantic model stored in Repo1. The changes will be built and deployed lo Workspace2 by using Azure Pipelines.
You need to ensure that report and semantic model definitions are saved as individual text files in a folder hierarchy. The solution must minimize development and maintenance effort.
In which file format should you save the changes?
- A. PBIT
- B. PBIP
- C. PBIDS
- D. PBIX
Answer: D
Explanation:
When working with Power BI Desktop and Git integration for version control, report and semantic model definitions should be saved in the PBIX format. PBIX is the Power BI Desktop file format that contains definitions for reports, data models, and queries, and it can be easily saved and tracked in a version-controlled environment. The solution should minimize development and maintenance effort, and saving in PBIX format allows for the easiest transition from development to deployment, especially when using Azure Pipelines for CI/CD (continuous integration/continuous deployment) practices.
References: The use of PBIX files with Power BI Desktop and Azure Repos for version control is discussed in Microsoft's official Power BI documentation, particularly in the sections covering Power BI Desktop files and Azure DevOps integration.
NEW QUESTION # 38
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