Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. B2B transformation
  8. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. 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
Data Integration
connections in the Target transformation.
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.

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