Table of Contents

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  1. Preface
  2. Introduction to Test Data Management
  3. Test Data Manager
  4. Projects
  5. Policies
  6. Data Discovery
  7. Creating a Data Subset
  8. Performing a Data Masking Operation
  9. Data Masking Techniques and Parameters
  10. Data Generation
  11. Data Generation Techniques and Parameters
  12. Working with Test Data Warehouse
  13. Analyzing Test Data with Data Coverage
  14. Plans and Workflows
  15. Monitor
  16. Reports
  17. ilmcmd
  18. tdwcmd
  19. tdwquery
  20. Data Type Reference
  21. Data Type Reference for Test Data Warehouse
  22. Data Type Reference for Hadoop
  23. Glossary

Advanced Masking Rules

Advanced Masking Rules

An advanced masking rule is a combination of masking techniques that mask multiple source columns or a target column based on values of more than one input column.
For example, you can create a full masked name by masking the first name and last name input columns. Define variable columns to contain the masked names. Add an output column that contains a result of an expression that combines the first name and last name variable columns.
Create the following types of columns in an advanced rule:
Input
The source column that you want to mask.
Variable
A column that contains intermediate values in a calculation. The variable column receives a value from an expression or a masking technique. You can configure multiple variable columns in order to combine multiple masking techniques.
Output
The target column that receives the masked value. The output column type contains a masking technique and masking parameters.