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. Data Sets
  13. Plans and Workflows
  14. Monitor
  15. Reports
  16. ilmcmd
  17. tdwcmd
  18. tdwquery
  19. Data Type Reference
  20. Data Type Reference for Test Data Warehouse
  21. Data Type Reference for Hadoop
  22. Glossary

Data Patterns for Random Generation

Data Patterns for Random Generation

You can enter data patterns from regular expressions to generate string and numeric data.
To generate numbers that contain special characters or any other operators, you use random string data generation technique. You can use the following operators to generate string data patterns:
. , \d , \w, (opt1| opt2|…..), {} , []
.
To generate numbers that do not contain special characters or any other operators, you use random numeric data generation technique. To generate numeric data, you can combine the following patterns:
\d, alternates (1|2|3|…), and [0-9]
. You cannot nest the alternates.
When you enter data patterns to generate the credit card number, Social Security number, and Social Insurance numbers, the generated data might not be valid. These numbers follow certain algorithms and you cannot use data patterns to generate valid numbers.