Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Aggregator transformation
  6. Cleanse transformation
  7. Data Masking transformation
  8. Deduplicate transformation
  9. Expression transformation
  10. Filter transformation
  11. Hierarchy Builder transformation
  12. Hierarchy Parser transformation
  13. Hierarchy Processor transformation
  14. Input transformation
  15. Java transformation
  16. Java transformation API reference
  17. Joiner transformation
  18. Labeler transformation
  19. Lookup transformation
  20. Mapplet transformation
  21. Normalizer transformation
  22. Output transformation
  23. Parse transformation
  24. Python transformation
  25. Rank transformation
  26. Router transformation
  27. Rule Specification transformation
  28. Sequence Generator transformation
  29. Sorter transformation
  30. SQL transformation
  31. Structure Parser transformation
  32. Transaction Control transformation
  33. Union transformation
  34. Velocity transformation
  35. Verifier transformation
  36. Web Services transformation

Transformations

Transformations

Target transformation

Target transformation

Use the Target transformation to define the target connection and target object for the mapping. You can use one or more Target transformations in a mapping.
Based on the connection type, you can define advanced target options, specify to use a new or existing target object, or configure update columns for the target. The target options that appear also depend on the connection type that you select. For example, when you select a Salesforce connection, you can configure success and error log details.
You can use file, database, and Informatica Cloud
Data Integration
connections in the Target transformation. If you create an
elastic mapping
, refer to
Administrator
in the Administrator help for information about supported connectors.
The following properties are available for the Target transformation:
  • General. Defines the transformation name and a description.
  • Incoming Fields. Includes the field rules that define the data written to the target. Allows a preview of target fields.
  • Target. Defines the target connection, target object, and advanced options. Based on the connection type, you can create a new target, use an existing target, or configure update columns.
  • Target Fields. Lists the fields in the target objects. Optionally add or remove fields. You can also edit target field metadata.
  • Field Mapping. Defines the field mappings from the upstream transformation to the target. Field mapping is only applicable when using an existing target object.

Target example

You might work with a flat file target in a mapping that reads Salesforce user account data but excludes user preference data. A Source transformation reads data from the Account object and the related User object.
The Target transformation uses a flat file connection that writes to the following directory:
C:\UserAccountData
. The default All Fields rule includes all incoming fields. You create a Named Field rule to exclude the unnecessary user preferences fields.
When you select
Create New Target at Runtime
, you enter the following name for the target file: SF_UserAccount_%d%m%y.csv.
The
mapping
task creates a target file named SF_UserAccount_291116.csv in the
C:\UserAccountData
directory when the task runs on November 29, 2016. The target file includes all fields from the Salesforce Account and User objects except for the user preferences fields specified in the Named Fields rule.