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. Appendix A: Data Type Reference
  21. Appendix B: Data Type Reference for Test Data Warehouse
  22. Appendix C: Data Type Reference for Hadoop
  23. Appendix D: Glossary

Data Masking Techniques and Parameters Overview

Data Masking Techniques and Parameters Overview

A data masking technique is the type of data masking to apply to a selected column. The masking parameters are the options that you configure for the technique.
The type of masking technique that you can apply depends on the datatype of the column that you need to mask. When you choose a masking technique, Test Data Manager displays parameters for the masking technique.
You can restrict the characters in a string to replace and the characters to apply in the mask. You can provide a range of numbers to mask numbers and dates. You can configure a range that is a fixed or percentage variance from the original number.
You can configure different masking parameters for a masking technique and save each configuration as a masking rule. The
Integration Service
modifies source data based on masking rules that you assign to each column. You can maintain data relationships in the masked data and maintain referential integrity between database tables.

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