Power BI Masterclass - Power BI Data Prep Challenge 3 - Count Customer Ratings and Sorting

The video tutorial guides viewers through analyzing product ratings using Excel and Power BI. It begins with an introduction to the ratings challenge, followed by importing and transforming data in Power BI. The tutorial covers splitting and cleaning data, creating visualizations, and sorting data for better insights. The instructor emphasizes the importance of maintaining original data integrity and demonstrates how to create a sorting table for custom sorting of ratings.

What is the main challenge discussed in the video regarding the Excel file?

• Counting different types of product ratings

• Finding the average price of products

• Identifying duplicate product codes

• Calculating the total cost of products

What is the first step in Power BI after importing the Excel data?

• Removing unnecessary columns

• Creating a new visualization

• Transforming the data

• Duplicating the product table

Why is it necessary to split the ratings column into rows?

• To remove duplicate entries

• To calculate the total cost

• To create a new table

• To ensure all ratings are in one column

What issue arises when splitting the ratings column by delimiter?

• The ratings are not split correctly

• The cost and price columns are removed

• Duplicate entries are created

• The original table is deleted

What is the purpose of creating a sorting table?

• To calculate the average rating

• To sort ratings alphabetically

• To adjust the order of ratings in the visualization

• To remove duplicate ratings

How is the sorting table used in the visualization?

• It is used to duplicate the ratings column

• It is used to calculate the total number of ratings

• It is used to create a new column for sorting

• It is used to filter out bad ratings

What is the correct order of ratings as specified in the sorting table?

• Good, Average, Bad, Excellent, OK

• Excellent, Good, OK, Average, Bad

• Average, Bad, Excellent, Good, OK

• OK, Excellent, Bad, Good, Average