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The Fuzzy Match Tool provides some pretty amazing flexibility for string joins with inexact values – usually in the case of names, addresses, phone numbers, or zip codes because many of the pre-configured match styles are designed around the formats of those types of string structures. However, taking advantage of the custom match style and carefully configuring the tool specific to human entered keyword strings in your data can also allow you to use the loose string matching feature of the tool to match those values to cleaner dictionary keyword strings. If done properly, it can help you take otherwise unusable strings and, matching by each individual word, recombine your human entered data to a standardized format that can be used in more advanced analyses.
In life, there are few things black and white. There are gray areas everywhere and the lines that separate can be a little fuzzy. The same holds true for data – especially when it’s human entered. That’s why we have the Fuzzy Match Tool – if your data isn’t clear as day, you can still get value out of your records by matching them to something a little more standardized.