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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Substitution Masking

Substitution Masking

Substitution masking replaces a column of data with similar but unrelated data. Use substitution masking to replace production data with realistic test data. When you configure substitution masking, define the dictionary that contains the substitute values.
The Data Masking transformation performs a lookup on the dictionary that you configure. The Data Masking transformation replaces source data with data from the dictionary. Dictionary files can contain string data, datetime values, integers, and floating point numbers. Enter datetime values in the following format:
mm/dd/yyyy
You can substitute data with repeatable or non-repeatable values. When you choose repeatable values, the Data Masking transformation produces deterministic results for the same source data and seed value. You must configure a seed value to substitute data with deterministic results.The Integration Service maintains a storage table of source and masked values for repeatable masking.
You can substitute more than one column of data with masked values from the same dictionary row. Configure substitution masking for one input column. Configure dependent data masking for the other columns that receive masked data from the same dictionary row.

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