Which type of data store should you recommend in the AnalyticsPOC workspace?
A.
a data lake
B.
a warehouse
C.
a lakehouse
D.
an external Hive metaStore
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 (Topic: demo questions)
What should you recommend using to ingest the customer data into the data store in the AnatyticsPOC workspace?
A.
a stored procedure
B.
a pipeline that contains a KQL activity
C.
a Spark notebook
D.
a dataflow
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 (Topic: demo questions)
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.
A.
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.
Question #4 (Topic: demo questions)
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.
A.
Correct Answer: A
Explanation:
Data Engineers: Read All SQL analytics endpoint data Data Analysts: Read All Apache Spark The permissions for the data store in the AnalyticsPOC workspace should align with the principle of least privilege: Data Engineers need read and write access but not to datasets or reports. Data Analysts require read access specifically to the dimensional model objects and the ability to create Power BI reports. Data Scientists need read access via Spark notebooks. These settings ensure each role has the necessary permissions to fulfill their responsibilities without exceeding their required access level.