Table of Contents


  1. Preface
  2. Working with Transformations
  3. Aggregator Transformation
  4. Custom Transformation
  5. Custom Transformation Functions
  6. Data Masking Transformation
  7. Data Masking Examples
  8. Expression Transformation
  9. External Procedure Transformation
  10. Filter Transformation
  11. HTTP Transformation
  12. Identity Resolution Transformation
  13. Java Transformation
  14. Java Transformation API Reference
  15. Java Expressions
  16. Java Transformation Example
  17. Joiner Transformation
  18. Lookup Transformation
  19. Lookup Caches
  20. Dynamic Lookup Cache
  21. Normalizer Transformation
  22. Rank Transformation
  23. Router Transformation
  24. Sequence Generator Transformation
  25. Sorter Transformation
  26. Source Qualifier Transformation
  27. SQL Transformation
  28. Using the SQL Transformation in a Mapping
  29. Stored Procedure Transformation
  30. Transaction Control Transformation
  31. Union Transformation
  32. Unstructured Data Transformation
  33. Update Strategy Transformation
  34. XML Transformations

Transformation Guide

Transformation Guide

Data Transformation Service Types

Data Transformation
Service Types

When you create a Data Processor transformation in Informatica Developer, you choose an object or component to define the transformation service type.
Data Transformation
has the following types of services that transform data:
  • Parser. Converts source documents to XML or JSON. The output of a parser is always XML. The input can have any format, such as text, HTML, Word, PDF, or HL7.
  • Serializer. Converts an XML or JSON file to an output document of any format. The output of a serializer can be any format, such as a text document, an HTML document, or a PDF.
  • Mapper and XMap. Converts an XML or JSON source document to another XML or JSON structure. A mapper processes the input similarly to a serializer. It generates output similarly to a parser. The input and the output are fully structured XML or JSON.
  • Transformer. Modifies the data in any format. Adds, removes, converts, or changes text. Use transformers with a parser, mapper, or serializer. You can also run a transformer as stand-alone component.
  • Streamer. Splits large input documents, such as multi-gigabyte data streams, into segments. The streamer processes documents that have multiple messages or records in them, such as HIPAA or EDI files.


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