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Summary

Identify a person multiple ways. Use this strategy when your matching business rules consist of multiple match criteria for identifying relationships, and you want to find the overlap between all of those definitions. 

Dataflow example using Associate, which cleanses party data and performs duplicate detection based on similar name and address, name and phone, or name and email, combining the three matching results to uncover hidden duplicates, using an Associate transform after the matching process..

Input

For the MatchAssociative configuration

 

Output

The Associate transform requres that you map one field on Output: Group_Number, which is the group number resulting from the association process. Records that belong to the same match group share the same group number. The group numbers start with the number one. Unique records have a blank group number.

Options

Options: The Priority_Value output field, the record priority value assigned to record, is available when you add a Group Prioritization operation to an Associate transform.




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