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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q85-Q90):

NEW QUESTION # 85
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 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.show()
Does this meet the goal?

A. Yes
B. No

Answer: B

NEW QUESTION # 86
You need to refresh the Orders table of the Online Sales department. The solution must meet the semantic model requirements. What should you include in the solution?

A. an Azure Data Factory pipeline that executes a dataflow to retrieve the maximum value of the OrderlD column in the destination lakehouse
B. an Azure Data Factory pipeline that executes a Stored procedure activity to retrieve the maximum value of the OrderlD column in the destination lakehouse
C. an Azure Data Factory pipeline that executes a Stored procedure activity to retrieve the minimum value of the OrderiD column m the destination lakehouse
D. an Azure Data Factory pipeline that executes a dataflow to retrieve the minimum value of the OrderlD column in the destination lakehouse

Answer: A

Explanation:
Requirement: "The number of rows added to the Orders table during refreshes must be minimized." The Orders table has a sequential OrderID.
To minimize refresh size, you must only import new rows, not the entire table.
This requires retrieving the maximum OrderID currently loaded, then only loading rows with a greater OrderID.
So, the correct solution is to use a pipeline (ADF) with a dataflow to retrieve the maximum OrderID.
The answer: C. an Azure Data Factory pipeline that executes a dataflow to retrieve the maximum value of
the OrderID column in the destination lakehouse

NEW QUESTION # 87
You are the administrator of a Fabric workspace that contains a lakehouse named Lakehouse1. Lakehouse1 contains the following tables:
* Table1: A Delta table created by using a shortcut
* Table2: An external table created by using Spark
* Table3: A managed table
You plan to connect to Lakehouse1 by using its SQL endpoint. What will you be able to do after connecting to Lakehouse1?

A. Update the data in Table1.
B. ReadTable2.
C. Update the data Table3.
D. ReadTable3.

Answer: A

NEW QUESTION # 88
You have a Fabric workspace that contains a DirectQuery semantic model. The model queries a data source that has 500 million rows.
You have a Microsoft Power Bl report named Report1 that uses the model. Report! contains visuals on multiple pages.
You need to reduce the query execution time for the visuals on all the pages.
What are two features that you can use? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A. query caching
B. OneLake integration
C. user-defined aggregations
D. automatic aggregation

Answer: C,D

Explanation:
User-defined aggregations (A) and query caching (C) are two features that can help reduce query execution time. User-defined aggregations allow precalculation of large datasets, and query caching stores the results of queries temporarily to speed up future queries. References = Microsoft Power BI documentation on performance optimization offers in-depth knowledge on these features.

NEW QUESTION # 89
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.

Answer:

Explanation:

Reference:
Query folding in Power Query
Power Query M formula language

NEW QUESTION # 90
......

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