Data analysis in Power BI Microsoft Quiz Answers

Get Data analysis in Power BI Microsoft Quiz Answers

Report authors can use more features to enhance their reports for analytical insights in their data with features like Q&A and exporting. In this module, you will closely examine your data and Power BI reports and then extract value with deeper analysis. Additionally, you will learn how to sort data and how to present the report in a cohesive manner. You will learn how to get a statistical summary for your data and export data from Power BI. You will also apply and perform advanced analytics on the report for deeper and more meaningful data insights.

This learning path can help you prepare for the Microsoft Certified: Data Analyst Associate certification.

This learning path helps prepare you for Exam PL-300: Microsoft Power BI Data Analyst.

Prerequisites:

None

Enroll on Microsoft

Module 1: Perform analytics in Power BI

You will learn how to use Power BI to perform data analytical functions, how to identify outliers in your data, how to group data together, and how to bin data for analysis. You will also learn how to perform time series analysis. Finally, you will work with advanced analytic features of Power BI, such as Quick Insights, AI Insights, and the Analyze feature.

Learning objectives:

In this module, you will:

• Explore statistical summary.
• Identify outliers with Power BI visuals.
• Group and bin data for analysis.
• Apply clustering techniques.
• Conduct time series analysis.
• Use the Analyze feature.
• Use advanced analytics custom visuals.
• Review Quick insights.
• Apply AI Insights.

Prerequisites:

None

Quiz 1: Check your knowledge

Q1. What Power BI feature can give an in-depth analysis of the distribution of data?

• The Next Level of Hierarchy feature can give in-depth analysis because it will allow you to drill down for all subcategories and is not used to analyze the distribution.
• The Analyze feature allows a user to understand why the distribution looks the way that it does.
• Only time series analysis can provide in-depth analysis on the data.

Q2. Where are time series charts located?

• The filter pane is where all filters on visuals and pages are located.
• Time series charts can be imported from AppSource.
• The fields pane is where all charts are located.

Q3. What visual should be used to display outliers?

• The line chart is best-suited to display outliers.
• The scatter chart is best-suited to display outliers.
• The clustered column chart is best-suited to display outliers.

Module 2: Work with AI visuals in Power BI

This module describes the AI capabilities of Power BI.

Learning objectives:

In this module, you will:

• Use the Q&A visual.
• Find important factors with the Key influencers visual.
• Use the Decomposition Tree visual to break down a measure.

Prerequisites:

None

Quiz 1: Check your knowledge

Q1. What does the AI splits feature do?

• AI splits work by considering all available fields and determining which one to drill into and will only return the highest or lowest value within your dataset.
• AI splits work by considering all available fields and determining which one to drill into to get the highest/lowest value of the measure that is being analyzed.
• AI splits only display the difference between highest and lowest value of the measure that is being analyzed.

Q2. Can you access the Q&A feature by using buttons?

• No, to use the Q&A feature, you will need to add the Q&A visual to your reporting canvas.
• Yes, you can access the Q&A feature by selecting Q&A button type.
• Yes, you can, but you will need to add the Q&A visual to your reporting canvas and then link your button with the visual that you have added.

Q3. Which of the following selections are not features of the Q&A visual?

• Adding new synonyms to fields through Q&A tooling.
• Converting a Q&A answer into a visual inside your report.
• Searching for help topics about Power BI.

Q4. What does the decomposition tree NOT enable you to do?

• Conduct root cause analysis to understand a measure better.
• Conduct what-if analysis with built-in parameters.
• Automatically analyze selected dimensions to find where a measure is highest or lowest.

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