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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

User Guide

User Guide

Data Masking Components

Data Masking Components

To perform data masking operations, assign rules to data domains, policies, and columns. Use data domains and data discovery to find columns that you want to mask. Create cascades to mask similar columns.
The following table describes the components that you create to implement data masking operations:
Component
Description
Assignments
The allocation of rules to a column to mask the column data.
You assign a rule to a column through either a column assignment or a data domain assignment. A column assignment assigns a rule directly to a column in a source. A data domain assignment assigns one or more rules in a data domain to columns in a source.
Column sensitivity
A sensitive column contains sensitive data. Configure column sensitivity to mark columns that you want to mask.
Data domain
An object that represents the functional meaning of a column based on the column data or the column name. Use a data domain to filter the ports that you want to mask when you assign a rule to columns. Define patterns in the data or patterns in the column names when you configure a data domain.
Plan
Defines data masking operations. A data masking plan indicates
whether to mask data in place in the source database or in stream in a target database
.
Policy
Defines the data masking rules, the data to mask, and the masking parameters for a source.
Rule
Defines the data masking technique, an optional rule qualifier, and masking parameters.
A masking technique defines the logic that is used to mask the data.
Masking parameters define how a masking technique in a rule masks source data.
You can set an override option in a rule that defines whether users can modify the masking parameters for the rule when they assign the rule to columns in a source.
Value cascade
Masks similar columns across tables. You can identify similar columns in a project and configure them to cascade masking rules. Use cascades when some fields are denormalized across multiple tables.

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