Learn how to manage potential matches in the new view of the Potential Matches perspective.

In an organization, entity or profile details are maintained across systems. Sometimes, multiple records of the same entity exist across these source systems. The records can belong to the same entity, but have certain inconsistencies between them. For example, one copy of the record can have the complete address or the correct phone number as compared to the others. This leads to confusion since we aren’t sure if the records belong to the same entity or if the information available in a record is correct.

In such cases, it would be beneficial to merge these records and maintain one record with the complete information.

Match them and then merge them

Reltio supports the concept of matching and merging. Matching refers to the process of identifying records that are considered similar and meet the matching requirement. You can create a process where you identify attributes that you use to match records. These attributes in turn compare profiles and determine if they’re a match. If the process determines that the records are a perfect match, they’re automatically merged. In other words, we can say that the system is confident that these records belong to the same entity and merges them. For more information, see topic Reltio Match, Merge and Survivorship.

Now, what happens when some records do look like a match, but don’t fully satisfy the matching requirements because of incomplete data? What does Reltio do when it isn’t fully confident about a record being a perfect match and automatically merge it? These records are termed as Potential Matches and they’re sent to data stewards for manual intervention. A data steward is given the task to review these matches manually, and then decide if they’re a match or not a match.

These potential matches are displayed in the Potential Match Review page. The data steward can review these records here and then determine further action.