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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. Macro Transformation
  30. Match Transformation
  31. Match Transformations in Field Analysis
  32. Match Transformations in Identity Analysis
  33. Normalizer Transformation
  34. Merge Transformation
  35. Parser Transformation
  36. Python Transformation
  37. Rank Transformation
  38. Read Transformation
  39. Relational to Hierarchical Transformation
  40. REST Web Service Consumer Transformation
  41. Router Transformation
  42. Sequence Generator Transformation
  43. Sorter Transformation
  44. SQL Transformation
  45. Standardizer Transformation
  46. Union Transformation
  47. Update Strategy Transformation
  48. Web Service Consumer Transformation
  49. Parsing Web Service SOAP Messages
  50. Generating Web Service SOAP Messages
  51. Weighted Average Transformation
  52. Window Transformation
  53. Write Transformation
  54. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Transformation Descriptions

Transformation Descriptions

The Developer tool contains common and data quality transformations. Data quality transformations are available in Data Engineering Quality.
The following table describes each transformation:
Transformation
Type
Description
Address Validator
Active or Passive
Verifies and enhances the accuracy of postal address records, and adds information that helps users to select the mail recipients and to deliver the mail.
Association
Active
Creates links between the duplicate records that a Match transformation assigns to different clusters.
Aggregator
Active
Performs aggregate calculations.
Bad Record Exception
Active
Identifies records that might contain data errors, and loads the records to tables that an Analyst tool user can review and update.
Case Converter
Passive
Standardizes the case of strings.
Classifier
Passive
Writes labels that summarize the information in input port fields. Use when the fields contain significant amounts of text.
Comparison
Passive
Generates numeric scores that indicate the degree of similarity between pairs of input strings.
Consolidation
Active
Creates a consolidated record from records identified as duplicates by the Match transformation.
Data Masking
Passive
Replaces sensitive production data with realistic test data for non-production environments.
This transformation can be connected or unconnected within the pipeline.
Data Processor
Active
Processes unstructured and semi-structured file formats in a mapping.
Decision
Passive
Evaluates conditions in input data and creates output based on the results of those conditions.
Duplicate Record Exception
Active
Identifies records that might contain duplicate information, and loads the records to tables that an Analyst tool user can review and update.
Expression
Passive
Calculates a value.
Filter
Active
Filters data.
Hierarchical to Relational
Active
Processes hierarchical input and transforms it into relational output.
Java
Active or Passive
Executes user logic coded in Java. The repository stores the byte code for the user logic.
Joiner
Active
Joins data from different databases or flat file systems.
Key Generator
Active
Assigns records to groups based on data values in a column that you select.
Labeler
Passive
Writes labels that describe the characters or strings in an input port field.
Lookup
Active or Passive
Look up and return data from a flat file, logical data object, reference table, relational table, view, or synonym.
This transformation can be connected or unconnected within the pipeline.
Macro
Passive
Enables dynamic functionality for a mapplet.
Match
Active
Generates scores that indicate the degrees of similarity between input records.
Merge
Passive
Reads the data values from multiple input columns and creates a single output column.
Normalizer
Active
Processes source rows that contain multiple-occurring data and returns a target row for each instance of the multiple-occurring data.
Output
Passive
Defines mapplet output rows.
Parser
Passive
Parses the values on an input port into separate output ports based on the types of information that the values contain.
Rank
Active
Limits records to a top or bottom range.
Read
Passive
Reads data from a source.
Relational to Hierarchical
Active
Processes relational input and transforms it into hierarchical output.
REST Web Service Consumer
Active
Connects to a REST web service as a web service client to access or transform data
Router
Active
Routes data into multiple transformations based on group conditions.
Sequence Generator
Passive
Generates a numeric sequence of values.
Sorter
Active
Sorts data based on a sort key.
SQL
Active or Passive
Executes SQL queries against a database.
Standardizer
Passive
Generates standardized versions of input strings.
Union
Active
Merges data from different databases or flat file systems.
Update Strategy
Active
Determines whether to insert, delete, update, or reject rows.
Web Service Consumer
Active
Connects to a web service as a web service client to access or transform data.
Weighted Average
Passive
Reads the match scores that a Match transformation generates for the records in a data set, and calculates an average score for each pair of records. You can apply different weights to the scores that the transformation generates for each pair of records.
Write
Passive
Represents a target that the mapping writes data to.

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