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

Transformations

Transformations

Normalized fields

Normalized fields

Define the fields to be normalized on the
Normalized Fields
tab. You can also include other incoming fields that you want to use in the mapping.
When you define normalized fields, you can create fields manually or select fields from a list of incoming fields. When you create a normalized field, you can set the data type to String or Number, and then define the precision and scale.
In advanced mode, you can use any primitive data type.
In advanced mode, the Normalizer transformation produces multiple output groups. Otherwise, the Normalizer transformation produces only one output group.
When incoming fields include multiple-occurring fields without a corresponding category field, you can create the category field to define the occurs for the data. For example, to represent three fields with different types of income, you can create an Income category field and set the occurs value to 3.

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