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Microsoft DP-600 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Prepare data: In this topic, questions about creating objects in a lakehouse or warehouse, copying data, transforming data, and optimizing performance appear.
Thema 2	Implement and manage semantic models: The topic delves into designing and building semantic models, and optimizing enterprise-scale semantic models.
Thema 3	Maintain a data analytics solution: This section is all about implementing security and governance. In this topic, you also get information about maintaining the analytics development lifecycle.

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric DP-600 Prüfungsfragen mit Lösungen (Q149-Q154):

149. Frage
You plan to use Fabric to store data.
You need to create a data store that supports the following:
- Writing data by using T-SQL
- Multi-table transactions
- Dynamic data masking
Which type of data store should you create?

A. KQL database
B. warehouse
C. lakehouse
D. semantic model

Antwort: B

150. Frage
You have a Fabric workspace named Workspace1.
You need to create a semantic model named Model1 and publish Model1 to Workspace1. The solution must meet the following requirements:
- Can revert to previous versions of Model1 as required.
- Identifies differences between saved versions of Model1.
- Uses Microsoft Power Bl=I Desktop to publish to Workspace1.
- Can edit item definition files by using Microsoft Visual Studio Code.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Save Model1 in Power BI Desktop as a PBIP file.
B. Save Model1 in Power BI Desktop as a PBIT file.
C. Enable users to edit data models in the Power BI service.
D. Enable Git integration for Workspace1.

Antwort: A,D

151. Frage
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.

Antwort:

Begründung:

Explanation:

* You should use CREATE VIEW to make the pricing group logic available for T-SQL queries.
* The CASE statement should be used to determine the pricing group based on the list price.
The T-SQL statement should create a view that classifies products into pricing groups based on the list price.
The CASE statement is the correct conditional logic to assign each product to the appropriate pricing group.
This view will standardize the pricing group logic across different databases and semantic models.

152. Frage
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?

A. The column has missing values.
B. All the table rows are profiled.
C. The column has duplicate values.
D. There are 935 values that occur only once.

Antwort: C

Begründung:
The pickupLongitude column has duplicate values. This can be inferred because the 'Distinct count' is 935 while the 'Count' is 1000, indicating that there are repeated values within the column. Reference = Microsoft Power BI documentation on data profiling could provide further insights into understanding and interpreting column statistics like these.

153. Frage
You have a Fabric tenant that contains a workspace named Workspace