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 Generation Components

Data Generation Components

To perform data generation operations, assign rules to columns. Import metadata to define the columns in the target database.
The following table describes the components that you create to implement data generation:
Component
Description
Assignments
The allocation of rules to a column to generate the column data.
Plan
Defines data generation operations. You import the target schema metadata into the repository in the plan and configure the settings.
Rule
Defines the data generation technique and parameters.
A generation technique defines the logic to generate the data. Generation parameters define how a generation technique in a rule generates data.
You can set an override option in a rule that defines whether users can modify the generation parameters for the rule when they assign the rule to the columns in a target.
Table
The target table in which you assign a generation rule.
Entity
Defines a set of tables that are related based on physical or logical constraints.
You cannot perform data generation operations that include an entity if the primary key column is a computed column.