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Microsoft DP-600 Exam Syllabus Topics:

Topic	Details
Topic 1	Prepare data: In this topic, questions about creating objects in a lakehouse or warehouse, copying data, transforming data, and optimizing performance appear.
Topic 2	Implement and manage semantic models: The topic delves into designing and building semantic models, and optimizing enterprise-scale semantic models.
Topic 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 Sample Questions (Q111-Q116):

NEW QUESTION # 111
You have a Fabric tenant that contains a lakehouse named Lakehouse1
Readings from 100 loT devices are appended to a Delta table in Lakehouse1. Each set of readings is approximately 25 KB. Approximately 10 GB of data is received daily.
All the table and SparkSession settings are set to the default.
You discover that queries are slow to execute. In addition, the lakehouse storage contains data and log files that are no longer used.
You need to remove the files that are no longer used and combine small files into larger files with a target size of 1 GB per file.
What should you do? To answer, drag the appropriate actions to the correct requirements. Each action may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 112
You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.
You need to write a DAX query that will be executed by using the XMLA endpoint. The query must return the total amount of sales from the same period last year.
How should you complete the DAX expression? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 113
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 .sumary ()
Does this meet the goal?

A. Yes
B. No

Answer: A

NEW QUESTION # 114
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.

A. Update the effective end date of rows when the non-key attribute values have changed.
B. Insert new rows when the natural key exists in the dimension table, and the non-key attribute values have changed.
C. Insert new records when the natural key is a new value in the table.
D. Update rows when the non-key attributes have changed.

Answer: C,D

Explanation:
Type 1 SCD does not preserve history, therefore no end dates for table entries exists.

NEW QUESTION # 115
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a subfolder named Subfolder1 that contains CSV files. You need to convert the CSV files into the delta format that has V-Order optimization enabled. What should you do from Lakehouse explorer?

A. Use the Optimize feature.
B. Create a new shortcut in the Tables section.
C. Create a new shortcut in the Files section.
D. Use the Load to Tables feature.

Answer: D

NEW QUESTION # 116
......

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