Prepare DP-600 Exam with Using DP-600 Dump Questions

1. You have a Fabric tenant that contains a complex semantic model. The model is based on a star schema and contains many tables, including a fact table named Sales. You need to create a diagram of the model. The diagram must contain only the Sales table and related tables.

What should you use from Microsoft Power Bl Desktop?

2. You have a Fabric tenant that contains two workspaces named Woritspace1 and Workspace2. Workspace1 contains a lakehouse named Lakehouse1. Workspace2 contains a lakehouse named Lakehouse2. Lakehouse! contains a table named dbo.Sales. Lakehouse2 contains a table named dbo.Customers.

You need to ensure that you can write queries that reference both dbo.Sales and dbo.Customers in the same SQL query without making additional copies of the tables.

What should you use?

3. 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.

4. You have a Fabric tenant that contains a warehouse named Warehouse!. Warehousel contains two schemas name schemal and schema2 and a table named schemal.city.

You need to make a copy of schemal.city in schema2. The solution must minimize the copying of data.

Which T-SQL statement should you run?

5. 1. Topic 1, Contoso 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.

6. 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)

7. You have a Microsoft Power Bl report named Report1 that uses a Fabric semantic model.

Users discover that Report1 renders slowly.

You open Performance analyzer and identify that a visual named Orders By Date is the slowest to render.

The duration breakdown for Orders By Date is shown in the following table.





What will provide the greatest reduction in the rendering duration of Report1?

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

9. You have a semantic model named Model 1. Model 1 contains five tables that all use Import mode. Model1 contains a dynamic row-level security (RLS) role named HR. The HR role filters employee data so that HR managers only see the data of the department to which they are assigned.

You publish Model1 to a Fabric tenant and configure RLS role membership. You share the model and related reports to users.

An HR manager reports that the data they see in a report is incomplete.

What should you do to validate the data seen by the HR Manager?

10. HOTSPOT

You have a Fabric tenant that contains a warehouse named WH1. You run the following T-SQL query against WH1.





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

11. You have a Fabric tenant that uses a Microsoft tower Bl Premium capacity. You need to enable scale-out for a semantic model.

What should you do first?

12. You have a Fabric tenant

You plan to create a data pipeline named Pipeline1. Pipeline1 will include two activities that will execute in sequence. You need to ensure that a failure of the first activity will NOT block the second activity.

Which conditional path should you configure between the first activity and the second activity?

13. HOTSPOT

You have a Fabric workspace that uses the default Spark starter pool and runtime version 1,2.

You plan to read a CSV file named Sales.raw.csv in a lakehouse, select columns, and save the data as a Delta table to the managed area of the lakehouse. Sales_raw.csv contains 12 columns.

You have 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.

14. Which T-SQL function is best suited for retrieving current data alongside historical data in a temporal table in Microsoft Fabric?

15. What is the primary function of the XMLA endpoint in Microsoft Fabric?

16. DRAG DROP

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.

17. HOTSPOT

You have a Fabric tenant that contains a semantic model named model1.

The two largest columns in model1 are shown in the following table.





You need to optimize model 1.

The solution must meet the following requirements:

• Reduce the model size.

• Increase refresh performance when using Import mode.

• Ensure that the datetime value for each sales transaction is available in the model.

What should you do on each column? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

18. 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.

19. HOTSPOT

You have a Fabric tenant that contains a lakehouse.

You are using a Fabric notebook to save a large DataFrame by using 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.

20. 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?

21. HOTSPOT

You have a Fabric warehouse that contains a table named Sales.Products. Sales.Products contains the following columns.





You need to write a T-SQL query that will return the following columns.





How should you complete the code? To answer, select the appropriate options in the answer area.

22. You have an Amazon Web Services (AWS) subscription that contains an Amazon Simple Storage Service (Amazon S3) bucket named bucketl.

You have a Fabric tenant that contains a lakehouse named LH1.

In LH1, you plan to create a OneLake shortcut to bucketl.

You need to configure authentication for the connection.

Which two values should you provide? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

23. 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.

24. 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?

25. 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?

26. HOTSPOT

You have a Fabric workspace named Workspace1 and an Azure Data Lake Storage Gen2 account named storage"!. Workspace1 contains a lakehouse named Lakehouse1.

You need to create a shortcut to storage! in Lakehouse1.

Which connection and endpoint should you specify? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

27. 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?

28. 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.

29. You have a Fabric tenant that contains a semantic model. The model contains 15 tables.

You need to programmatically change each column that ends in the word Key to meet the following requirements:

• Hide the column.

• Set Nullable to False.

• Set Summarize By to None

• Set Available in MDX to False.

• Mark the column as a key column.

What should you use?

30. You have a Microsoft Power Bl 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?

31. 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.

32. HOTSPOT

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 the total amount of sales from the same period last year.

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

33. HOTSPOT

You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named Lakehouse1 and a warehouse named Warehouse1.

You need to create a new table in Warehouse1 named POSCustomers by querying the customer table in Lakehouse1.

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.

34. You have a Fabric tenant that contains a data warehouse.

You need to load rows into a large Type 2 slowly changing dimension (SCD). The solution must minimize resource usage.

Which T-SQL statement should you use?

35. What type of data store is best used for handling large volumes of both structured and unstructured data in Microsoft Fabric?

36. 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 for 45 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?