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. Data Subset
  8. Data Masking
  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

Data Masking Task Flow

Data Masking Task Flow

To implement data masking operations, assign masking rules to columns in a source. Create a plan and add policies and rules to the plan. Generate a workflow from the plan to mask data in a target database.
Complete the following high-level steps to create the components that you need in a data masking plan:
  1. Create rules, data domains, and policies to define the masking techniques and masking parameters.
  2. Create a project that contains one or more data sources.
  3. Add policies to the project. When you add a policy to a project, the project receives the data domains and the rules that the policy contains.
  4. Add additional rules to the project. When you add additional rules to a project, the project receives the masking rules.
  5. Assign rules to columns in the source. You can assign rules from a policy or data domain. You can assign the default rules from data domains to multiple columns at a time. Manually assign advanced rules and mapplet rules to columns.
  6. Create a plan and add data masking components to the plan. Generate a workflow from the plan. Monitor the progress of the workflow in the
    Monitor
    view or in the
    Plan
    view.