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NEW QUESTION 52
You are configuring a Power Bl report for accessibility as shown in the following table.

You need to change the default colors of all three visuals to make the report more accessible to users who have color vision deficiency. Which two settings should you configure in the Customize theme window? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

  • A. First-level elements colors
  • B. Sentiment colors
  • C. Divergent colors
  • D. Theme colors

Answer: B,D

 

NEW QUESTION 53
Which two possible tools can you use to identify what causes the report to render slowly? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Azure Data Studio
  • B. Synapse Studio
  • C. Performance analyzer in Power Bl Desktop
  • D. DAX Studio

Answer: C,D

Explanation:
Some users indicate that the visuals in Power BI reports are slow to render when making filter selections.
B: You can investigate a slow query in a Power BI report using DAX Studio, looking at the query plan and the server timings.
D: Use Power BI Desktop Performance Analyzer to optimize the report or model.
Reference:
https://docs.microsoft.com/en-us/power-bi/guidance/report-performance-troubleshoot

 

NEW QUESTION 54
You have a dataset that contains a table named UserPermissions. UserPermissions contains the following data.

You plan to create a security role named User Security for the dataset. You need to filter the dataset based on
the current users. What should you include in the DAX expression?

  • A. [User] = USERNAMEQ()
  • B. [UserPermissions] – USERNAME()
  • C. [User] = USEROBJECTID()
  • D. [UserPermissions] – USERPRINCIPALNAME()
  • E. [User] = USERPRINCIPALNAME()

Answer: A

 

NEW QUESTION 55
You are using a Python notebook in an Apache Spark pool in Azure Synapse Analytics.
You need to present the data distribution statistics from a DataFrame in a tabular view.
Which method should you invoke on the DataFrame?

  • A. rollup
  • B. freqlcems
  • C. summary
  • D. corr

Answer: D

Explanation:
pandas.DataFrame.corr computes pairwise correlation of columns, excluding NA/null values.
Incorrect:
* freqItems
pyspark.sql.DataFrame.freqItems
Finding frequent items for columns, possibly with false positives. Using the frequent element count algorithm described in https://doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou.’
* summary is used for index.
* There is no panda method for rollup. Rollup would not be correct anyway.

 

NEW QUESTION 56
You develop a solution that uses a Power Bl Premium capacity. The capacity contains a dataset that is
expected to consume 50 GB of memory.
Which two actions should you perform to ensure that you can publish the model successfully to the Power Bl
service? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. Publish an initial dataset that is less than 10 GB.
  • B. Increase the Max Offline Dataset Size setting.
  • C. Restart the capacity.
  • D. Publish the complete dataset.
  • E. Invoke a refresh to load historical data based on the incremental refresh policy.

Answer: C,D

 

NEW QUESTION 57
……

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