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Hello – I need help working with a fuzzy match tool to help match the franchise name to the LFA name in the best way possible. Could you please help me build this. Below is a sample of the data, but there are thousands of rows in my sheet. Typically I would want to match the Franchise Name to the LFA since it is a 1 to many relationship. Do you have any suggestions on how to configure the fuzzy match tool to get the most accurate results possible?
Just for clarity Anderson County would match to all 3 Anderson county’s on the left, but there are also some instances where you could have Philadelphia (Area 1), Philadelphia (Area 2), that would need to match to Area’s 1 and 2 on the Franchise name side as well.
To do the fuzzy match you need to union these two streams together into one column, for example name. You will also need a source field, so you could determine where the name came from (Source values would be LGA and Franchisee). To create that field source and name you can just transpose. I would then separate the two though to create a record ID on each stream. Make sure the record IDs for one of the streams starts at a different spot, for example 1,000,000 and then counts up from there. Then union back together and perform the fuzzy match with record ID , Source, and Name as the fuzzy match. You can modify it as such for names, nicknames, numbers, etc. Play around with it. Then you will get an output score, join these output scores based on IDs back to the original dataset to finish.
Fuzzy match is not perfect so do not expect perfection from this.