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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. Data Type Reference
  21. Data Type Reference for Test Data Warehouse
  22. Data Type Reference for Hadoop
  23. Glossary

Data Masking Techniques

Data Masking Techniques

You can apply masking techniques based on the source datatype that you configure for a column. For example, if the column datatype is numeric, you can define a masked value that is within a fixed or percent variance from the original value.
The
PowerCenter Integration Service
does not mask integers greater than 28 characters.
The following table describes the masking techniques that you can choose when you define a rule:
Masking Technique
Description
Advanced
Applies masking techniques to multiple input and output columns. You can create an expression to combine multiple columns. You can mask all datatypes.
Credit card
Applies a built-in mask format to disguise credit card numbers. You can mask the string datatype.
Email address
Applies a built-in mask format to disguise email addresses. You can mask the string datatype.
Encryption
Applies encryption to the source data. You can assign an encryption method to mask the data with. You can encrypt string data types.
Expression
Applies an expression to a column to create or disguise data. Use expression masking if the expression references one column. If the expression includes multiple columns, use the calculated masking technique with advanced masking. You can mask all datatypes.
IP address
Applies a built-in mask format to disguise IP addresses. You can mask the string datatype.
Key
Produces deterministic results for the same source data, masking rules, and seed value. You can mask date, numeric, and string datatypes.
Mapplet
Applies masking rules from a mapplet. The mapplet contains the logic to mask the input columns and return data to the target. A mapplet can have multiple input and output columns.
Nullification
Replaces a column of data with a null value. You can mask all datatypes.
Phone
Applies a built-in mask format to disguise phone numbers. You can mask the string datatype.
Random
Produces random, non-repeatable results for the same source data and masking rules. You can mask date, numeric, and string datatypes.
Shuffle
Applies sensitive column values from one row to another row in the same table. You can restrict which rows to shuffle data from. You can mask date, numeric, and string datatypes.
SIN
Applies a mask to Social Insurance numbers. You can mask a string datatype.
SSN
Applies a built-in mask format to disguise Social Security numbers. You can mask the string datatype.
Substitution
Replaces a column of data with similar but unrelated data from a dictionary. You can mask date, numeric, and string datatypes.
URL
Applies a built-in mask format to disguise URL data. You can mask a string datatype.