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. Plans and Workflows
  11. Monitor
  12. Reports
  13. ilmcmd
  14. Data Type Reference
  15. Data Type Reference for Hadoop

Data Masking Overview

Data Masking Overview

Use data masking to replace source data in sensitive columns with realistic test data for nonproduction environments. When you create data masking rules, you define the logic to replace sensitive data. To configure the sensitive columns that you want to mask, assign data masking rules to source columns, data domains, and policies.
A policy defines the data masking rules, the data to mask, and the masking parameters for a source. When you assign data masking rules to policies, you can assign multiple source columns to the data masking rules. You can also assign a rule directly to a source column. You can assign data masking rules based on the data type of the source columns.
To implement data masking, create a data masking plan and generate a workflow from the plan. A data masking plan can contain policies and rules. In a data masking plan, select a rule that is assigned to a column. Policies and rules define how to mask sensitive and confidential data in a target database. A data masking plan contains at least one rule or one policy.
When you start the workflow, the
Data Integration Service
performs the masking operation.