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

1. You have a Fabric tenant that contains a lakehouse named Lakehouse1.

You need to prevent new tables added to Lakehouse1 from being added automatically to the default semantic model of the lakehouse.

What should you configure? (5)

2. HOTSPOT

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.

3. 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.

4. Which type of data store should you recommend in the AnalyticsPOC workspace?

5. You have a Fabric tenant that contains a lakehouse. You plan to use a visual query to merge two tables.

You need to ensure that the query returns all the rows that are present in both tables.

Which type of join should you use?

6. You have a Fabric tenant that contains a data pipeline.

You need to ensure that the pipeline runs every four hours on Mondays and Fridays.

To what should you set Repeat for the schedule?

7. 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.

8. 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.

9. 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?

10. 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.

11. You have a Fabric tenant that contains a semantic model named Model1. Model1 uses Import mode.

Model1 contains a table named Orders. Orders has 100 million rows and the following fields.





You need to reduce the memory used by Model! and the time it takes to refresh the model.

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

12. You have a Fabric tenant that contains a warehouse.

Several times a day. the performance of all warehouse queries degrades. You suspect that Fabric is throttling the compute used by the warehouse.

What should you use to identify whether throttling is occurring?

13. 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?

14. You have a Fabric tenant that contains a Microsoft Power Bl report.

You are exploring a new semantic model.

You need to display the following column statistics:

• Count

• Average

• Null count

• Distinct count

• Standard deviation

Which Power Query function should you run?

15. DRAG DROP

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.

16. 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?

17. 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.

18. 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?

19. 1. 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 AnalyticsPOC 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 AnalyticsPOC 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 AnalyticsPOC 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 AnalyticsPOC 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 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.

20. HOTSPOT

You have a Fabric tenant that contains a warehouse named Warehouse1. Warehouse1 contains a fact table named FactSales that has one billion rows. You run the following T-SQL statement. CREATE TABLE test.FactSales AS CLONE OF Dbo.FactSales;

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE:

Each correct selection is worth one point.

21. DRAG DROP

You are implementing a medallion architecture in a single Fabric workspace.

You have a lakehouse that contains the 8ronze and Silver layers and a warehouse that contains the Gold layer.

You create the items required to populate the layers as shown in the following table.





You need to ensure that the layers are populated daily in sequential order such that Silver is populated only after Bronze is complete, and Gold is populated only after Silver is complete. The solution must minimize development effort and complexity.

What should you use to execute each set of items? To answer, drag the appropriate options to the correct items. Each option 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.

22. 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.

23. 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?

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

What should you do?