Fuzzy Matching is a tool that provide a method to process phrases or strings from the database finding matches between two elements. It also provides the score to show up the accuracy of the match by choose the threshold.

Eventually you are going to get some dataset that need to be matched but the description of fields is not standardised as an example below:

 

Now what could be done to fix this issue and match those elements?

Using the Fuzzy Matching tool, it can be fixed. Fuzzy Matching will be able to retrieve the correct description even if it has some difference between them. Fuzzy Matching also provides score to measure the accuracy that have between the matches.

Here is an example of the workflow using the Fuzzy Matching to fix this type of problem:

How to configure Fuzzy Match.

  • Choose the merge/Purge Model (in this example above the merge was chosen because the idea is to make comparison between records from different sources):

 

 

  • Select Source ID field:

  • Select the record ID filed and the percentage to match threshold:

  • Select “Filed name”, “Match Style” and make some “Edit” in Match Fields option:

  • In “Edit Match Options” is possible you to choose the match function as you can see below:

  • Select the “Advanced Options”:

After these steps, your Fuzzy Matching is configured to run and make the magic happening.

The Fuzzy Matching will bring all the results in the percentage that has been set in the match threshold.

In the example below, as a result of the Fuzzy Matching work, the field “Product from the table 1” (source One) and the field “Product from Table 2” (source two) were matched and also the percentage of matches from the field “Max_MatchScore” was given to see the accuracy of the match.

We went through the concept of Fuzzy matching, the practical application. I hope you had a good time reading about Fuzzy Matching.