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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Aggregator Transformation
  4. Classifier Transformation
  5. Cleanse transformation
  6. Comparison Transformation
  7. Custom Transformation
  8. Custom Transformation Functions
  9. Consolidation Transformation
  10. Data Masking Transformation
  11. Data Masking Examples
  12. Decision Transformation
  13. Dynamic Lookup Cache
  14. Expression Transformation
  15. External Procedure Transformation
  16. Filter Transformation
  17. HTTP Transformation
  18. Identity Resolution Transformation
  19. Java Transformation
  20. Java Transformation API Reference
  21. Java Expressions
  22. Java Transformation Example
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Match Transformation
  29. Match Transformations in Field Analysis
  30. Match Transformations in Identity Analysis
  31. Merge Transformation
  32. Normalizer Transformation
  33. Parse transformation
  34. Rank Transformation
  35. Router Transformation
  36. Rule Specification transformation
  37. Sequence Generator Transformation
  38. Sorter Transformation
  39. Source Qualifier Transformation
  40. SQL Transformation
  41. Using the SQL Transformation in a Mapping
  42. Stored Procedure Transformation
  43. Standardizer Transformation
  44. Transaction Control Transformation
  45. Union Transformation
  46. Unstructured Data Transformation
  47. Update Strategy Transformation
  48. Verifier transformation
  49. Weighted Average Transformation
  50. XML Transformations

Transformation Guide

Transformation Guide

Rule Specification transformation

Rule Specification transformation

The Rule Specification transformation adds a rule specification asset that you created in
Data Quality
to a mapping.
A rule specification is a set of one or more logical operations that analyze data according to business criteria that you define. The rule specification generates an output that indicates whether the data satisfies the business criteria. The rule specification can also update the data that it analyzes. You define the logical operations as IF/THEN/ELSE statements in
Data Quality
.
Each Rule Specification transformation can contain a single rule specification. You can add multiple Rule Specification transformations to a mapping.
Use a Rule Specification transformation to accomplish the following goals:
  • Define the types of data that a business data set contains.
  • Define a set of conditions that the business data must satisfy.
  • Define the actions to take when the data satisfies the conditions of the business rule.
  • Define the actions to take when the data fails to satisfy the conditions of the business rule.
A Rule Specification transformation is similar to a Mapplet transformation, as it allows you to add data analysis and data transformation logic that you designed elsewhere to a mapping. Like mapplets, rule specifications are reusable assets. A Rule Specification transformation shows incoming and outgoing fields. It does not display the logic that the rule specification contains or allow to you edit the rule specification. To edit the rule specification, open it in
Data Quality
.
To use the Rule Specification transformation, you need the appropriate license.

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