Demo Microsoft DP-600 Exam Questions

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Section: Practice Mode 4 Questions
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Question 1

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

Correct Answer: C
Explanation:
A lakehouse (C) should be recommended for the AnalyticsPOC workspace. It combines the
capabilities of a data warehouse with the flexibility of a data lake. A lakehouse supports semistructured
and unstructured data and allows for T-SQL and Python read access, fulfilling the technical 
requirements outlined for Litware. Reference = For further understanding, Microsoft's
documentation on the lakehouse architecture provides insights into how it supports various data
types and analytical operations
Question 2

What should you recommend using to ingest the customer data into the data store in the
AnatyticsPOC workspace?

Correct Answer: D
Explanation:
For ingesting customer data into the data store in the AnalyticsPOC workspace, a dataflow (D) should
be recommended. Dataflows are designed within the Power BI service to ingest, cleanse, transform,
and load data into the Power BI environment. They allow for the low-code ingestion and
transformation of data as needed by Litware's technical requirements. Reference = You can learn
more about dataflows and their use in Power BI environments in Microsoft's Power BI
documentation.
Question 3

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.

Correct Answer: A
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.

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