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  • Informatica Data Quality 10.4.0
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Table of Contents

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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Back Next

Create the Data Processor Transformation

Create the Data Processor Transformation

Create a Data Processor transformation in the Developer tool. If you create a blank Data Processor transformation, you must then create a Script, XMap, Library, or Validation Rules object in the transformation. Alternatively, you can use the New Transformation wizard to auto-generate a Data Processor transformation.
  1. In the Developer tool, click
    File
    New
    Transformation
    .
  2. Select the Data Processor transformation and click
    Next
    .
  3. Enter a name for the transformation and browse for a Model repository location to put the transformation.
  4. Select whether to create Data Processor transformation with a wizard or to create a blank Data Processor transformation.
  5. If you selected to create a blank Data Processor transformation, click
    Finish
    .
    The Developer tool creates the empty transformation in the repository. The
    Overview
     view appears in the Developer tool.
  6. If you selected to create an Data Processor transformation with a wizard, perform the following steps:
    1. Click
      Next
      .
    2. Select an input format.
    3. Browse to select a schema, copybook, example file, or specification file if required for certain input formats such as COBOL, JSON, or ASN.1.
    4. Select an output format.
    5. Browse to select a schema, copybook, example file, or specification file if required for the output format.
    6. Click
      Finish
      . The wizard creates the transformation in the repository.
    The transformation might contain a Parser, Serializer, Mapper, or an object with common components. If you selected a schema, copybook, example file, or specification file the wizard also creates a schema in the repository that is equivalent to the hierarchy in the file.
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