Power BI Masterclass - Power BI Data Prep Challenge 5 - Handling Missing Values in Power BI

The video tutorial covers handling missing values in data using Power BI. It begins with an introduction to missing values and common methods to address them, such as using the mean or median. The instructor then presents a data example involving fruit sales and demonstrates how to import and transform this data in Power BI. The tutorial explains calculating averages for missing values and replacing nulls using M code. Finally, it shows how to finalize the data and create visualizations, including using slicers and formatting options.

What is a common method to handle missing values in data analysis?

• Deleting the entire dataset

• Using statistical measures like mean or median

• Ignoring the missing values

• Filling with random numbers

In the dataset used in the tutorial, what type of products are being analyzed?

• Electronics

• Fruits

• Vehicles

• Clothing

What tool is used to import and transform data in Power BI?

• Query Editor

• Data Navigator

• Excel Connector

• Data Importer

How can you identify missing values in Power BI's query editor?

• By checking the data type

• By using a filter

• By sorting the data

• By looking for a black bar indicator

What statistical measure is used to fill missing values in this tutorial?

• Standard Deviation

• Median

• Mode

• Mean

What is the first step in filling missing values with averages in Power BI?

• Creating a new table

• Highlighting all columns

• Deleting null entries

• Exporting data to Excel

After calculating averages, what is the next step to fill missing values?

• Replace nulls with zeros

• Export data to a CSV file

• Use the calculated average column

• Delete the average column

What should be done with the average column after filling missing values?

• Keep it for future reference

• Remove it as it's no longer needed

• Export it to a new file

• Rename it for clarity

What is the purpose of unpivoting data in Power BI?

• To format data for better analysis

• To create a new table

• To delete unnecessary columns

• To merge datasets

How can you visualize the cleaned data in Power BI?

• By using a line graph

• By exporting to Excel

• By creating a simple table

• By using a pie chart