Hi, I'm Ask INFA!
What would you like to know?
ASK INFAPreview
Please to access Ask INFA.

Table of Contents

Search

  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

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.

0 COMMENTS

We’d like to hear from you!