Reliable DP-600 Dumps Pdf, Certification DP-600 Questions

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Microsoft DP-600 Practice Exams For Self-Assessment (Web-Based And Desktop)

The Microsoft DP-600 certification exam is one of the hottest and career-oriented certifications in the market. This Implementing Analytics Solutions Using Microsoft Fabric (DP-600) certification exam has been inspiring beginners and experienced professionals since its beginning. Over this long time period, countless Implementing Analytics Solutions Using Microsoft Fabric (DP-600) exam candidates have passed their Implementing Analytics Solutions Using Microsoft Fabric (DP-600) certification exam, and now they are offering their services to the top world brands.

Microsoft DP-600 Exam Syllabus Topics:

Topic	Details
Topic 1	Explore and analyze data: It also deals with performing exploratory analytics. Moreover, the topic delves into query data by using SQL.
Topic 2	Prepare and serve data: In this topic, questions about creating objects in a lakehouse or warehouse, copying data, transforming data, and optimizing performance appear.
Topic 3	Implement and manage semantic models: The topic delves into designing and building semantic models, and optimizing enterprise-scale semantic models.
Topic 4	Plan, implement, and manage a solution for data analytics: Planning a data analytics environment, implementing and managing a data analytics environment are discussed in this topic. It also focuses on managing the analytics development lifecycle.

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q61-Q66):

NEW QUESTION # 61
You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1. Report1 includes a Python visual. Data displayed by the visual is grouped automatically and duplicate rows are NOT displayed. You need all rows to appear in the visual. What should you do?

A. Reference the columns in the Python code by index.
B. Add a unique field to each row.
C. Modify the Summarize By property for all columns.
D. Modify the Sort Column By property for all columns.

Answer: B

NEW QUESTION # 62
You have a Fabric workspace named Workspace1 that contains a data flow named Dataflow1. Dataflow1 contains a query that returns the data shown in the following exhibit.

You need to transform the date columns into attribute-value pairs, where columns become rows.
You select the VendorlD column.
Which transformation should you select from the context menu of the VendorlD column?

A. Group by
B. Remove other columns
C. Unpivot columns
D. Unpivot other columns
E. Split column

Answer: C

Explanation:
The transformation you should select from the context menu of the VendorID column to transform the date columns into attribute-value pairs, where columns become rows, is Unpivot columns (B). This transformation will turn the selected columns into rows with two new columns, one for the attribute (the original column names) and one for the value (the data from the cells). Reference = Techniques for unpivoting columns are covered in the Power Query documentation, which explains how to use the transformation in data modeling.

NEW QUESTION # 63
You are analyzing customer purchases in a Fabric notebook by using PySpanc You have the following DataFrames:

You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling. You write the following code.

Which code should you run to populate the results DataFrame?

Answer: D

Explanation:
The correct code to populate the results DataFrame with minimal data shuffling is Option A. Using the broadcast function in PySpark is a way to minimize data movement by broadcasting the smaller DataFrame ( customers) to each node in the cluster. This is ideal when one DataFrame is much smaller than the other, as in this case with customers. References = You can refer to the official Apache Spark documentation for more details on joins and the broadcast hint.

NEW QUESTION # 64
You have a Fabric tenant that contains a Microsoft Power Bl report named Report 1.
Report1 is slow to render. You suspect that an inefficient DAX query is being executed.
You need to identify the slowest DAX query, and then review how long the query spends in the formula engine as compared to the storage engine.
Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:
To identify the slowest DAX query and analyze the time it spends in the formula engine compared to the storage engine, you should perform the following actions in sequence:
* From Performance analyzer, capture a recording.
* View the Server Timings tab.
* Enable Query Timings and Server Timings. Run the query.
* View the Query Timings tab.
* Sort the Duration (ms) column in descending order by DAX query time.

NEW QUESTION # 65
You have a Fabric tenant that contains a semantic model.
You need to prevent report creators from populating visuals by using implicit measures.
What are two tools that you can use to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A. Microsoft Power BI Desktop
B. Microsoft SQL Server Management Studio (SSMS)
C. Tabular Editor
D. DAX Studio

Answer: A,C

Explanation:
Microsoft Power BI Desktop (A) and Tabular Editor (B) are the tools you can use to prevent report creators from using implicit measures. In Power BI Desktop, you can define explicit measures which can be used in visuals. Tabular Editor allows for advanced model editing, where you can enforce the use of explicit measures. Reference = Guidance on using explicit measures and preventing implicit measures in reports can be found in the Power BI and Tabular Editor official documentation.

NEW QUESTION # 66
......

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