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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

Creating a Write Transformation from a Data Object

Creating a Write Transformation from a Data Object

You can create and configure a Write transformation in the mapping editor.
You might want to use this method if you want to configure specific properties for the transformation. For example, you can create the transformation, and then configure it to get column metadata from the data source at run time.
  1. Right-click in the mapping editor and select
    Add Transformation
    .
    The
    Add Transformation
     dialog box opens.
  2. Select
    Write
     and click
    OK
    .
    The
    New Write Transformation
     wizard opens.
  3. Select
    Physical Data Object
     or
    Logical Data Object
    , and then click
    Browse
    .
    The
    Select Data Object
     dialog box opens.
  4. Select a data source, and then click
    OK
    .
  5. To define Write transformation columns by the associated data object, select
    Associated data object
    .
    The Write transformation ports are the same as the columns of the associated data object.
  6. To dynamically update target object columns at run time with changes from the target file, select
    At run-time, get data object columns from data source
    .
    The Data Integration Service refreshes the column metadata for the Write transformation when the mapping runs.
  7. Click
    Finish
    .
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