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I know that this topic has been discussed in a couple ways already but I think/hope my question is slightly different to warrant a new thread. I have applicant data out of an ATS and need to normalize employer names. For example I followed a fuzzy match workflow and received the following results for the employer Lowe's. The fuzzy match workflow that I followed worked to a very small degree but I still have a ton of variety with Lowe's. I have similar issues with Wal Mart and Target. Does anyone have a suggestion on how to standardize or normalize employer name data?
Unfortunately, I don't have anything more than employer data. Any suggestions would be greatly appreciated. I'm still learning the logic behind the Fuzzy Match tool and know this may not be possible.
I don't think you're going to get there based on Fuzzy Match alone :(
What I usually do in this case is create a reference/conversion table that has all the Lowes values in one column (like what you have already) and the second column is what you want them to be converted to (say "Lowes Companies Incorporated"). You would then join on to this table to get the new value. You would also check the records that DON'T join, because those ones have to be added to the table because they are not already there.
@cmcclellan, I agree with you for sure. But what would you suggest when I am working with thousands of entries? Should I run the Fuzzy match workflow and maybe take the top 10 employers and then build out a list from there?