Hi, I'm Ask INFA!
What would you like to know?
ASK INFAPreview
Please to access Ask INFA.

Table of Contents

Search

  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

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.
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.
  • Merge the cleansed data from two or more input fields into a single new output field.
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.
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
.

0 COMMENTS

We’d like to hear from you!