Quiz 2025 Efficient DP-600: Certification Implementing Analytics Solutions Using Microsoft Fabric Dump

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Microsoft DP-600 Exam Syllabus Topics:

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

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q57-Q62):

NEW QUESTION # 57
You have a Fabric tenant that contains a complex semantic model. The model is based on a star schema and contains many tables, including a fact table named Sales. You need to create a diagram of the model. The diagram must contain only the Sales table and related tables. What should you use from Microsoft Power Bl Desktop?

A. DAX query view
B. data categories
C. Model view
D. Data view

Answer: C

Explanation:
To create a diagram that contains only the Sales table and related tables, you should use the Model view (C) in Microsoft Power BI Desktop. This view allows you to visualize and manage the relationships between tables within your semantic model. References = Microsoft Power BI Desktop documentation outlines the functionalities available in Model view for managing semantic models.

NEW QUESTION # 58
You have a Fabric tenant that contains a semantic model. The model contains 15 tables.
You need to programmatically change each column that ends in the word Key to meet the following requirements:
* Hide the column.
* Set Nullable to False.
* Set Summarize By to None
* Set Available in MDX to False.
* Mark the column as a key column.
What should you use?

A. DAX Studio
B. ALM Toolkit
C. Tabular Editor
D. Microsoft Power Bl Desktop

Answer: C

Explanation:
Tabular Editor is an advanced tool for editing Tabular models outside of Power BI Desktop that allows you to script out changes and apply them across multiple columns or tables. To accomplish the task programmatically, you would:
* Open the model in Tabular Editor.
* Create an Advanced Script using C# to iterate over all tables and their respective columns.
* Within the script, check if the column name ends with 'Key'.
* For columns that meet the condition, set the properties accordingly: IsHidden = true, IsNullable = false, SummarizeBy = None, IsAvailableInMDX = false.
* Additionally, mark the column as a key column.
* Save the changes and deploy them back to the Fabric tenant.
References: The ability to batch-edit properties using scripts in Tabular Editor is well-documented in the tool's official documentation and user community resources.

NEW QUESTION # 59
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1.
You are creating a new data pipeline.
You plan to copy external data to Table1. The schema of the external data changes regularly.
You need the copy operation to meet the following requirements:
* Replace Table1 with the schema of the external data.
* Replace all the data in Table1 with the rows in the external data.
You add a Copy data activity to the pipeline. What should you do for the Copy data activity?

A. From the Destination tab, set Table action to Overwrite.
B. From the Source tab, add additional columns.
C. From the Source tab, select Enable partition discovery
D. From the Source tab, select Recursively
E. From the Settings tab, select Enable staging

Answer: A

NEW QUESTION # 60
You have a Fabric tenant that contains a lakehouse.
You are using a Fabric notebook to save a large DataFrame by using the following code.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
* The results will form a hierarchy of folders for each partition key. - Yes
* The resulting file partitions can be read in parallel across multiple nodes. - Yes
* The resulting file partitions will use file compression. - No
Partitioning data by columns such as year, month, and day, as shown in the DataFrame write operation, organizes the output into a directory hierarchy that reflects the partitioning structure. This organization can improve the performance of read operations, as queries that filter by the partitioned columns can scan only the relevant directories. Moreover, partitioning facilitates parallelism because each partition can be processed independently across different nodes in a distributed system like Spark. However, the code snippet provided does not explicitly specify that file compression should be used, so we cannot assume that the output will be compressed without additional context.
References =
* DataFrame write partitionBy
* Apache Spark optimization with partitioning

NEW QUESTION # 61
Hotspot Question
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:

NEW QUESTION # 62
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Quiz 2025 Efficient DP-600: Certification Implementing Analytics Solutions Using Microsoft Fabric Dump

2025 Certification DP-600 Dump Pass Certify | Professional New DP-600 Test Discount: Implementing Analytics Solutions Using Microsoft Fabric

Microsoft DP-600 Exam Syllabus Topics:

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q57-Q62):

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