1. (LO 2.4) The Chapter 2 Problem data set contains a list of outstanding invoices for a fic- DATA VISUALIZATION tional company, but the data aren’t ready for analysis yet. Load this file into Power BI and validate and clean the data. Several of these steps will be repeated from Problems 6 and 7, and it is important to learn how to make these adjustments using different tools. Once you have cleaned the data in Power BI, you will create a visualization. Take the following steps:

a. In the Navigator window, select Suggest Tables > Table 1 (Sheet 1).

b. Click Transform Data to open the Power Query Editor.

c. Notice that Power BI automatically standardized the date format in the Due Date column.

d. Right-click the Days Past Due column and select Replace Values to find and replace the string “ days” (include the leading space). Type days with a leading space in the Value to Find field and leave the Replace With field empty to remove the unnecessary string.

e. Adjust the Days Past Due field to a numerical data type.

f. Right-click the Customer field and select Transform to trim and clean the data. Select both options for Trim and Clean.

g. Click Close & Apply to begin exploratory analysis.

h. Place a check mark next to Customer and next to Days Past Due.

i. In the Values field, right-click Days Past Due to adjust the summary measure to Maximum.

This will display the customers with the invoices that are the most days past due.