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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

Transformation types

Transformation types

After you add a transformation to a mapping, you can define transformation details. Each transformation type has a unique set of options that you can configure.
The transformations that you can use in a mapping depend on the mapping type.
The following table provides a brief description of each transformation:
Transformation
Description
Source
Reads data from a source.
Target
Writes data to a target.
Aggregator
An active transformation that performs aggregate calculations on groups of data.
Cleanse
A passive transformation that adds a cleanse asset that you created in
Data Quality
to a mapping or mapplet. Use a cleanse asset to standardize the form and content of your data.
Data Masking
A passive transformation that masks sensitive data as realistic test data for nonproduction environments.
Deduplicate
An active transformation that adds a deduplicate asset that you created in
Data Quality
to a mapping or mapplet. Use a deduplicate asset to find instances of duplicate identities in a data set and optionally to consolidate the duplicates into a single record.
Expression
A passive transformation that performs calculations on individual rows of data.
Filter
An active transformation that filters data from the data flow.
Hierarchy Builder
An active transformation that converts relational input into hierarchical output.
Hierarchy Parser
A passive transformation that converts hierarchical input into relational output.
Hierarchy Processor
An active transformation that converts hierarchical input into relational output, relational input into hierarchical output, or hierarchical output into hierarchical output of a different schema.
Input
A passive transformation that passes data into a mapplet. Can be used in a mapplet, but not in a mapping.
Java
Executes user logic coded in Java.
Can be active or passive.
Joiner
An active transformation that joins data from two sources.
Labeler
A passive transformation that adds a labeler asset that you created in
Data Quality
to a mapping or mapplet. Use a labeler asset to identify the types of information in an input field and to assign labels for each type to the data.
Lookup
Looks up data from a lookup object. Defines the lookup object and lookup connection. Also defines the lookup condition and the return values.
A passive lookup transformation returns one row. An active lookup transformation returns more than one row.
Mapplet
Inserts a mapplet into a mapping or another mapplet. A mapplet contains transformation logic that you can create and use to transform data before it is loaded into the target.
Can be active or passive based on the transformation logic in the mapplet.
Normalizer
An active transformation that processes data with multiple-occurring fields and returns a row for each instance of the multiple-occurring data.
Output
A passive transformation that passes data from a mapplet to a downstream transformation. Can be used in a mapplet, but not in a mapping.
Parse
A passive transformation that adds a parse asset that you created in
Data Quality
to a mapping or mapplet. Use a parse asset to parse the words or strings in an input field into one or more discrete output fields based on the types of information that the words or strings contain.
Python
Runs Python code that defines transformation functionality. Can be active or passive.
Rank
An active transformation that limits records to a top or bottom range.
Router
An active transformation that you can use to apply a condition to incoming data.
Rule Specification
A passive transformation that adds a rule specification asset that you created in
Data Quality
to a mapping or mapplet. Use a rule specification asset to apply the data requirements of a business rule to a data set.
Sequence Generator
A passive transformation that generates a sequence of values.
Sorter
A passive transformation that sorts data in ascending or descending order, according to a specified sort condition.
SQL
Calls a stored procedure or function or executes a query against a database.
Passive when it calls a stored procedure or function. Can be active or passive when it processes a query.
Structure Parser
A passive transformation that analyzes unstructured data from a flat file source and writes the data in a structured format.
Transaction Control
An active transformation that commits or rolls back sets of rows during a mapping run.
Union
An active transformation that merges data from multiple input groups into a single output group.
Velocity
A passive transformation that executes a Velocity script to convert JSON or XML hierarchal input from one format to another without flattening the data.
Verifier
A passive transformation that adds a verifier asset that you created in
Data Quality
to a mapping or mapplet. Use a verifier asset to verify and enhance postal address data.
Web Services
An active transformation that connects to a web service as a web service client to access, transform, or deliver data.