Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Aggregator Transformation
  4. Custom Transformation
  5. Custom Transformation Functions
  6. Data Masking Transformation
  7. Data Masking Examples
  8. Expression Transformation
  9. External Procedure Transformation
  10. Filter Transformation
  11. HTTP Transformation
  12. Identity Resolution Transformation
  13. Java Transformation
  14. Java Transformation API Reference
  15. Java Expressions
  16. Java Transformation Example
  17. Joiner Transformation
  18. Lookup Transformation
  19. Lookup Caches
  20. Dynamic Lookup Cache
  21. Normalizer Transformation
  22. Rank Transformation
  23. Router Transformation
  24. Sequence Generator Transformation
  25. Sorter Transformation
  26. Source Qualifier Transformation
  27. SQL Transformation
  28. Using the SQL Transformation in a Mapping
  29. Stored Procedure Transformation
  30. Transaction Control Transformation
  31. Union Transformation
  32. Unstructured Data Transformation
  33. Update Strategy Transformation
  34. XML Transformations

Transformation Guide

Transformation Guide

Masking Types

Masking Types

The masking type is the type of data masking to apply to the selected column. Select one of the following masking types:
  • Key masking. Produces deterministic results for the same source data, masking rules, and seed value.
  • Substitution masking. Replaces a column of data with similar but unrelated data from a dictionary.
  • Dependent masking. Replaces the values of one source column based on the values of another source column.
  • Random masking. Produces random results for the same source data and masking rules.
  • Expression masking. Applies an expression to a port to change the data or create data.
  • Special mask formats. Applies special mask formats to common types of sensitive data. You can mask social security numbers, social insurance numbers, credit card numbers, phone numbers, URL addresses, email addresses, or IP addresses.
  • Substitution. Replaces a column of data with similar but unrelated data from a dictionary.
  • No Masking. The Data Masking transformation does not change the source data.
Default is No Masking.

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