Microsoft Certification DP-600 Exam Dumps

1. What should you recommend using to ingest the customer data into the data store in the Anatytics POC workspace?

2. Which type of data store should you recommend in the Analytics POC workspace?

3. You need to recommend a solution to prepare the tenant for the PoC.

Which two actions should you recommend performing from the Fabric Admin portal? Each correct answer presents part of the solution. NOTE: Each correct answer is worth one point.

4. You need to ensure the data loading activities in the Analytics POC workspace are executed in the appropriate sequence. The solution must meet the technical requirements.

What should you do?

5. You need to implement the date dimension in the data store. The solution must meet the technical requirements.

What are two ways to achieve the goal? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

6. HOTSPOT

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.

7. Topic 2, Contoso, ltd.



Overview

Contoso, ltd. is a US-based health supplements company, Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.



Identity Environment

Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroupi and ReseachReviewefsGfoup2.



Data Environment

Contoso has the following data environment

• The Sales division uses a Microsoft Power B1 Premium capacity.

• The semantic model of the Online Sales department includes a fact table named Orders that uses import mode. In the system of origin, the OrderlD value represents the sequence in which orders are created.

• The Research department uses an on-premises. third-party data warehousing product.

• Fabric is enabled for contoso.com.

• An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Producthne1. The data is in the delta format.

• A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.



Planned Changes

Contoso plans to make the following changes:

• Enable support for Fabric in the Power Bl Premium capacity used by the Sales division.

• Make all the data for the Sales division and the Research division available in Fabric.

• For the Research division, create two Fabric workspaces named Producttmelws and Productline2ws.

• in Productlinelws. create a lakehouse named LakehouseV

• In Lakehouse1. create a shortcut to storage1 named ResearchProduct.



Data Analytics Requirements

Contoso identifies the following data analytics requirements:

• All the workspaces for the Sales division and the Research division must support all Fabric experiences.

• The Research division workspaces must use a dedicated, on-demand capacity that has per-minute billing.

• The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.

• For the Research division workspaces, the members of ResearchRevtewersGroupl must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.

• For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.

• All the semantic models and reports for the Research division must use version control that supports branching



Data Preparation Requirements

Contoso identifies the following data preparation requirements:

• The Research division data for Producthne2 must be retrieved from Lakehouset by using Fabric notebooks.

• All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.



Semantic Model Requirements

Contoso identifies the following requirements for implementing and managing semantic models;

• The number of rows added to the Orders table during refreshes must be minimized.

• The semantic models in the Research division workspaces must use Direct Lake mode.



General Requirements

Contoso identifies the following high-level requirements that must be considered for all solutions:

• Follow the principle of least privilege when applicable

• Minimize implementation and maintenance effort when possible.



Which syntax should you use in a notebook to access the Research division data for Productlinel?

A)





B)





C)





D)

8. HOTSPOT

You need to recommend a solution to group the Research division workspaces.

What should you include in the recommendation? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

9. HOTSPOT

Which workspace rote assignments should you recommend for ResearchReviewersGroupl and ResearchReviewersGroupZ? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

10. HOTSPOT

You need to migrate the Research division data for Productline2. The solution must meet the data preparation requirements.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

11. You need to ensure that Contoso can use version control to meet the data analytics requirements and the general requirements.

What should you do?

12. You need to recommend which type of fabric capacity SKU meets the data analytics requirements for the Research division.

What should you recommend?

13. You need to refresh the Orders table of the Online Sales department. The solution must meet the semantic model requirements.

What should you include in the solution?

14. What should you use to implement calculation groups for the Research division semantic models?

15. 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)

16. HOTSPOT

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.

17. HOTSPOT

You have a Fabric tenant.

You plan to create a Fabric notebook that will use Spark DataFrames to generate Microsoft Power Bl visuals.

You run the following code.





For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

18. 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?

19. 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?

20. 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.

21. 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?

22. 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 automatically and duplicate rows are NOT displayed. You need all rows to appear in the visual.

What should you do?

23. DRAG DROP

You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.

You need to write a DAX query that will be executed by using the XMLA endpoint The query must return a table of stores that have opened since December 1,2023.

How should you complete the DAX expression? 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.

24. 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?

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?

26. 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.

27. 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 Definition Language (TMDL) extension for Microsoft Visual Studio Code.

You need to save the semantic model to a file.

Which file format should you use?

28. HOTSPOT

You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains three schemas named schemaA, schemaB. and schemaC

You need to ensure that a user named User1 can truncate tables in schemaA only.

How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

29. You need to provide Power Bl developers with access to the pipeline.

The solution must meet the following requirements:

• Ensure that the developers can deploy items to the workspaces for Development and Test.

• Prevent the developers from deploying items to the workspace for Production.

• Follow the principle of least privilege.

Which three levels of access should you assign to the developers? Each correct answer presents part of the solution. NOTE: Each correct answer is worth one point.

30. Topic 1, Litware. Inc. Case Study



Overview

Litware. Inc. is a manufacturing company that has offices throughout North America. The analytics team at Litware contains data engineers, analytics engineers, data analysts, and data scientists.



Existing Environment

litware has been using a Microsoft Power Bl tenant for three years. Litware has NOT enabled any Fabric capacities and features.



Fabric Environment

Litware has data that must be analyzed as shown in the following table.





The Product data contains a single table and the following columns.







The customer satisfaction data contains the following tables:

• Survey

• Question

• Response



For each survey submitted, the following occurs:

• One row is added to the Survey table.

• One row is added to the Response table for each question in the survey.



The Question table contains the text of each survey question. The third question in each survey response is an overall satisfaction score. Customers can submit a survey after each purchase.



User Problems

The analytics team has large volumes of data, some of which is semi-structured. The team wants to use Fabric to create a new data store.

Product data is often classified into three pricing groups: high, medium, and low. This logic is implemented in several databases and semantic models, but the logic does NOT always match across

implementations.



Planned Changes

Litware plans to enable Fabric features in the existing tenant. The analytics team will create a new data store as a proof of concept (PoC). The remaining Litware users will only get access to the Fabric features once the PoC is complete. The PoC will be completed by using a Fabric trial capacity.



The following three workspaces will be created:

• AnalyticsPOC: Will contain the data store, semantic models, reports, pipelines, dataflows, and notebooks used to populate the data store

• DataEngPOC: Will contain all the pipelines, dataflows, and notebooks used to populate Onelake

• DataSciPOC: Will contain all the notebooks and reports created by the data scientists



The following will be created in the Analytics POC workspace:

• A data store (type to be decided)

• A custom semantic model

• A default semantic model

• Interactive reports



The data engineers will create data pipelines to load data to OneLake either hourly or daily depending on the data source. The analytics engineers will create processes to ingest transform, and load the data to the data store in the Analytics POC workspace daily. Whenever possible, the data engineers will use low-code tools for data ingestion. The choice of which data cleansing and transformation tools to use will be at the data engineers' discretion.

All the semantic models and reports in the Analytics POC workspace will use the data store as the sole data source.



Technical Requirements

The data store must support the following:

• Read access by using T-SQL or Python

• Semi-structured and unstructured data

• Row-level security (RLS) for users executing T-SQL queries

Files loaded by the data engineers to OneLake will be stored in the Parquet format and will meet Delta Lake specifications.

Data will be loaded without transformation in one area of the Analytics POC data store. The data will then be cleansed, merged, and transformed into a dimensional model.

The data load process must ensure that the raw and cleansed data is updated completely before populating the dimensional model.

The dimensional model must contain a date dimension. There is no existing data source for the date dimension. The Litware fiscal year matches the calendar year. The date dimension must always contain dates from 2010 through the end of the current year.

The product pricing group logic must be maintained by the analytics engineers in a single location. The pricing group data must be made available in the data store for T-SQL queries and in the default semantic model.



The following logic must be used:

• List prices that are less than or equal to 50 are in the low pricing group.

• List prices that are greater than 50 and less than or equal to 1,000 are in the medium pricing group.

• List pnces that are greater than 1,000 are in the high pricing group.



Security Requirements

Only Fabric administrators and the analytics team must be able to see the Fabric items created as part of the PoC. Litware identifies the following security requirements for the Fabric items in the Analytics POC workspace:

• Fabric administrators will be the workspace administrators.

• The data engineers must be able to read from and write to the data store. No access must be granted to datasets or reports.

• The analytics engineers must be able to read from, write to, and create schemas in the data store. They also must be able to create and share semantic models with the data analysts and view and modify all reports in the workspace.

• The data scientists must be able to read from the data store, but not write to it. They will access the data by using a Spark notebook.

• The data analysts must have read access to only the dimensional model objects in the data store. They also must have access to create Power Bl reports by using the semantic models created by the analytics engineers.

• The date dimension must be available to all users of the data store.

• The principle of least privilege must be followed.



Both the default and custom semantic models must include only tables or views from the dimensional model in the data store.



Litware already has the following Microsoft Entra security groups:

• FabricAdmins: Fabric administrators

• AnalyticsTeam: All the members of the analytics team

• DataAnalysts: The data analysts on the analytics team

• DataScientists: The data scientists on the analytics team

• Data Engineers: The data engineers on the analytics team

• Analytics Engineers: The analytics engineers on the analytics team



Report Requirements

The data analysis must create a customer satisfaction report that meets the following requirements:

• Enables a user to select a product to filter customer survey responses to only those who have purchased that product

• Displays the average overall satisfaction score of all the surveys submitted during the last 12 months up to a selected date

• Shows data as soon as the data is updated in the data store

• Ensures that the report and the semantic model only contain data from the current and previous year

• Ensures that the report respects any table-level security specified in the source data store

• Minimizes the execution time of report queries



HOTSPOT

You to need assign permissions for the data store in the Analytics POC 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.

31. HOTSPOT

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.

32. HOTSPOT

You need to resolve the issue with the pricing group classification.

How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.