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I've been working on a record linkage project, in order to drive decisions about record merges in a CRM database. We have recently upgraded to DSS 9.0.1. Is there anyone out there who has been successfully using the new Fuzzy Join Visual recipe to do this kind of thing?
Let's imagine for simplicity's sake that I have ~1/4 million records. I'd like to find those customers who are in reality very likely to be exactly the same customer. So that I can use special steps to merge these customers for data analytics.
Let's oversimplify... Imagine I had this table:
|5||Mary M Jonesfirstname.lastname@example.org|
I'm looking for a result table that shows
I don't want any of the self-joined rows (See Id in (1,2,4,7) or duplicates that start from already paired sets. (See ID in (3,5,6) )
To attempt to do this I'm trying to join a table to itself. Use the Fuzzy Join logic visual recipe.
My guess is that there might need to be several intermediate steps between source data and final data. That would be OK.
However, I've had several currently unresolved challenges using the New Fuzzy Join Recipe.
Looking forward to your thoughts.
To answer your questions:
The first two sound like what you need. You could combine them both in one filter recipe after the join with a condition: left_id < right_id. That would remove exact person matches and also permutations.
You were mentioning the errors, could you give more details about what didn't work?
One of the challenges with the Fuzzy Join visual recipes interface is that it only offers "Strict Equality". Nothing like the typical >, >=, !=, etc. So I don't see here how to implement your suggestions:
I'm on DSS V9.0.1
Maybe I miss understood. Are you are suggesting a post fuzzy join filter recipe with the ID< ID filter? I see.
I guess that I'd really like to do this in a single join. And hopefully, avoid doing some of the potential extra time-consuming compares.
Yes, I meant an extra recipe after the fuzzy join one.
Fuzzy join doesn't support post-filtering so there's no other way to do it.