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. B2B transformation
  8. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. 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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