Create a data coverage task to perform pairwise data analysis and to create a visual representation of the data coverage in a

data pack

. You can assess the quality of test data by analyzing combinations of values in any two columns. You can change the combinations to ensure that you cover all valid combinations of values. You can improve the quality of the data and move data across categories to meet the minimum data threshold that you require.

For example, you need to test a banking application that offers credit cards to customers. You create a

data pack

with tables that contain data related to the credit card types and the criteria for each. The data could include location and the minimum balance required for each type of card. The

data pack

also contains tables with customer information. To understand whether you have sufficient data for the different test cases, you need to analyze the amount of data that you have in different categories. For example, you need to know if you have sufficient data for each type of card in each location.

When you analyze the data, you also see if there is more data than what you require for some locations. You can then update the data records across columns or data ranges to ensure that you have sufficient data density for test cases.