Manually reviewing clusters of duplicate records
What problem are you facing?
As a Find duplicates user I want to be able to manually evaluate and change clusters of records where I think the rules have matched records incorrectly e.g. I've got a husband and wife in my data, both called M. Smith and they share the same postal address, email address and loyalty card number. They're not a duplicate so I need to be able to separate them into individual clusters.
What impact does this problem have on you/your business?
The rules do a great job identifying duplicates in vast majority of my data, but there are certain clusters where a manual review and update would improve the results ensuring all of my matches are correct.
Do you have any existing workarounds? If so, please describe those.
Adjusting the rules e.g. by making them stricter, I can influence a bit what records end up in one cluster but it's not always granular enough for very specific cases and can sometimes make overall results worse.
Do you have any suggestions to solve the problem? Feel free to add images if this helps.
Allowing me to make manual adjustments, like merging and de-merging records and also to compare and and match multiple records.