Table of Contents

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

Developer Transformation Guide

Developer Transformation Guide

Association Transformation Overview

Association Transformation Overview

The Association transformation processes output data from a Match transformation. It creates links between duplicate records that are assigned to different match clusters, so that these records can be associated together in data consolidation and master data management operations.
The Association transformation generates an
AssociationID
value for each row in a group of associated records and writes the ID values to an output port.
The Consolidation transformation reads the output from the Association transformation. Use a Consolidation transformation to create a master record based on records with common association ID values.
The Association transformation accepts string and numerical data values on input ports. If you add an input port of another data type, the transformation converts the port data values to strings.
The AssociationID output port writes integer data. The transformation can write string data on an AssociationID port if the transformation was configured in an earlier version of Informatica Data Quality.

Example: Associating Match Transformation Outputs

The following table contains three records that could identify the same individual:
ID
Name
Address
City
State
ZIP
SSN
1
David Jones
100 Admiral Ave.
New York
NY
10547
987-65-4321
2
Dennis Jones
1000 Alberta Ave.
New Jersey
NY
-
987-65-4321
3
D. Jones
Admiral Ave.
New York
NY
10547-1521
-
A duplicate analysis operation defined in a Match transformation does not identify all three records as duplicates of each other, for the following reasons:
  • If you define a duplicate search on name and address data, records 1 and 3 are identified as duplicates but record 2 is omitted.
  • If you define a duplicate search on name and Social Security number data, records 1 and 2 are identified as duplicates but record 3 is omitted.
  • If you define a duplicate search on all three attributes (name, address, and Social Security number), the Match transformation may identify none of the records as matches.
The Association transformation links data from different match clusters, so that records that share a cluster ID are given a common AssociationID value. In this example, all three records are given the same AssociationID, as shown in the following table:
ID
Name
Address
City
State
Zip
SSN
Name and Address Cluster ID
Name and SSN Cluster ID
Association ID
1
David Jones
100 Admiral Ave.
New York
NY
10547
987-65-4320
1
1
1
2
Dennis Jones
1000 Alberta Ave.
New Jersey
NY
-
987-65-4320
2
1
1
3
D. Jones
Alberta Ave.
New York
NY
10547-1521
-
1
2
1
You can consolidate the duplicate record data in the Consolidation transformation.

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