Table of Contents

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

Transformations

Transformations

Cleanse transformation

Cleanse transformation

The Cleanse transformation adds a cleanse asset that you created in
Data Quality
to a mapping. A cleanse asset is a set of data transformation operations that standardize the form and content of your data.
You add a single cleanse asset to a Cleanse transformation. You can map one or more input fields to a Cleanse asset in the mapping.
A cleanse asset can perform one or more of the following operations:
  • Change the character case of the input data.
  • Remove leading and trailing spaces from input data.
  • Remove values from the input data.
  • Find and replace values in the input data.
You can configure multiple operations in a cleanse asset, and you can add any type of operation to the asset multiple times. The mapping performs the operations on an input data field in a sequence that you define, so that a single cleanse asset can specify multiple changes to the input field data. You can add multiple Cleanse transformations to a mapping, so that you can apply standardization operations to multiple data fields.
The transformation is not certified for serverless runtime execution.
The following image shows a mapping in which multiple Cleanse transformations read data fields from a Source transformation and write standardized data to a Target transformation:
Each cleanse transformation in the mapping performs a different standardization operation. The source transformation provides an input to each cleanse transformation, and each cleanse transformation provides an output that links to a single target.
A Cleanse transformation is similar to a Mapplet transformation, as it allows you to add data transformation logic that you designed elsewhere to a mapping. Like mapplets, cleanse assets are reusable assets.
A Cleanse transformation does not display the logic that the cleanse asset contains or allow you to edit the cleanse asset. To edit the cleanse asset, open it in
Data Quality
.