Microsoft Implementing Analytics Solutions Using Microsoft Fabric - DP-600 Exam Practice Test

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.

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?

You have a Fabric workspace named Workspacel that uses the Premium Per User (PPU) license mode and contains a semantic model named Model1.
Large semantic model storage format is selected for Model 1.
You need to ensure that tables imported into Modell are written automatically to Delta tables in OneLake.
What should you do for Modell and Workspacel? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You have a semantic model named Model1 that contains data that relates to customers and their bank account balances.
Model1 has the following tables and columns.

A customer can have one or more accounts. Each account can be associated to multiple customers.
You need to ensure that users can query Model1 to identify the total transaction amounts by customer.
What should you add to Model1?

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?

You have a Fabric tenant that contains a warehouse. The warehouse uses row-level security (RLS). You create a Direct Lake semantic model that uses the Delta tables and RLS of the warehouse. When users interact with a report built from the model, which mode will be used by the DAX queries?

You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a table named Nyctaxi_raw. Nyctaxi_raw contains the following columns.

You create a Fabric notebook and attach it to lakehouse1.
You need to use PySpark code to transform the data. The solution must meet the following requirements:
* Add a column named pickupDate that will contain only the date portion of pickupDateTime.
* Filter the DataFrame to include only rows where fareAmount is a positive number that is less than 100.
How should you complete the code? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.

Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals.
More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
Your network contains an on-premises Active Directory Domain Services (AD DS) domain named contoso.
com that syncs with a Microsoft Entra tenant by using Microsoft Entra Connect.
You have a Fabric tenant that contains a semantic model.
You enable dynamic row-level security (RLS) for the model and deploy the model to the Fabric service.
You query a measure that includes the username () function, and the query returns a blank result.
You need to ensure that the measure returns the user principal name (UPN) of a user.
Solution: You update the measure to use the USEROBJECT () function.
Does this meet the goal?

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 solution must 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?

You have a Fabric tenant that contains a warehouse named DW1 and a lakehouse named LH1. DW1 contains a table named Sales.Product. LH1 contains a table named Sales.Orders.
You plan to schedule an automated process that will create a new point-in-time (PIT) table named Sales.
ProductOrder in DW1. Sales.ProductOrder will be built by using the results of a query that will join Sales.
Product and Sales.Orders.
You need to ensure that the types of columns in Sales. ProductOrder match the column types in the source tables. The solution must minimize the number of operations required to create the new table.
Which operation should you use?

You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD).
Which two actions should you include in the process? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric tenant that contains a semantic model named Model1.
You discover that the following query performs slowly against Model1.

You need to reduce the execution time of the query.
Solution: following code:

Does this meet the goal?

You plan to deploy Microsoft Power BI items by using Fabric deployment pipelines. You have a deployment pipeline that contains three stages named Development, Test, and Production. A workspace is assigned to each stage.
You need to provide Power BI 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.
Ensure that developers can view items in 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.

You have an Azure SQL database named DB1 and a Fabric workspace named Workspace1. Workspace 1 contains a lakehouse named LH1 and a Dataflow Gen2 named Dataflow1. Dataflow1 includes a query named Query1 that loads data from DB1. applies transformations to the data, and then filters the data.
You discover that Query1 loads all the data before applying the transformations.
You need to ensure that Query1 uses query folding.
What should you do?

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?