Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. Cleanse transformation
  8. Data Masking transformation
  9. Data Services transformation
  10. Deduplicate transformation
  11. Expression transformation
  12. Filter transformation
  13. Hierarchy Builder transformation
  14. Hierarchy Parser transformation
  15. Hierarchy Processor transformation
  16. Input transformation
  17. Java transformation
  18. Java transformation API reference
  19. Joiner transformation
  20. Labeler transformation
  21. Lookup transformation
  22. Machine Learning transformation
  23. Mapplet transformation
  24. Normalizer transformation
  25. Output transformation
  26. Parse transformation
  27. Python transformation
  28. Rank transformation
  29. Router transformation
  30. Rule Specification transformation
  31. Sequence Generator transformation
  32. Sorter transformation
  33. SQL transformation
  34. Structure Parser transformation
  35. Transaction Control transformation
  36. Union transformation
  37. Velocity transformation
  38. Verifier transformation
  39. Web Services transformation

Transformations

Transformations

Blurring

Blurring

Blurring creates an output value within a fixed or percent variance from the source data value. Configure blurring to return a random value that is close to the original value. You can blur numeric and date values.
Select a fixed or percent variance to blur a numeric source value. The low bound value is a variance below the source value. The high bound value is a variance above the source value. The low and high values must be greater than or equal to zero. When the Data Masking transformation returns masked data, the numeric data is within the range that you define.
You can mask a date as a variance of the source date by configuring blurring. Select a unit of the date to apply the variance to. You can select the year, month, day, hour, minute, or second. Enter the low and high bounds to define a variance above and below the unit in the source date. The Data Masking transformation applies the variance and returns a date that is within the variance.
For example, to restrict the masked date to a date within two years of the source date, select year as the unit. Enter two as the low and high bound. If a source date is February 2, 2006, the Data Masking transformation returns a date between February 2, 2004, and February 2, 2008.

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