Fuzzy match name cleansing

[spencer046]

Hello,

I am struggling for a long time with below Fuzzy matching. I have below dataset. This is already an output of a fuzzy match with matching for Name, City, State, Zip

Name	City	State	Zip
MIELE	Forest Park	IL	60130
MIELE BROADWAY	Forest Park	IL	60130
MIELE PARTNERS FULFILLMENT	Forest Park	IL	60130
MIELE PARTNERS WAREHOUSING	Forest Park	IL	60130

The output I am expecting is below, I want all the name to be same when the City State Zips are same:

Name	City	State	Zip
MIELE	Forest Park	IL	60130
MIELE	Forest Park	IL	60130
MIELE	Forest Park	IL	60130
MIELE	Forest Park	IL	60130

Any suggestion would be highly appreciated.

[pedrodrfaria]

Hi @spencer046 

You can definitely do a fuzzy matching logic to get to the point you want, however, if your only need is that specific, then you can just go ahead and use a much simpler logic:

Please let me know if you actually is required to do a fuzzy match or if the above solution does not solve your problem.

Please assign a solution to the post if your questions were answered.

Pedro.

[spencer046]

Hi @pedrodrfaria thank you so much. That's onw way of sorting that out, but I am more interested in learning if this can be sorted out using Fuzzy Matches. I also have names with different starts that have same city state zip. 

Los Angeles_CA_90023 BAY CITIES C O BARBARA
Los Angeles_CA_90023 DDC CALIFORNIA
Los Angeles_CA_90023 Dependable Distribution Center
Los Angeles_CA_90023 LOS ANGELES SERVICE CENTER
Los Angeles_CA_90023 MEILE

I need to have a functionality where it can group different names under one name for  same city state zip.

[pedrodrfaria]

In this case for example are you trying to march MIELE Forest Park IL 60 130 with MEILE Los Angeles CA 90 023 ?

Just as a tip, the more complex you make the fuzzy matching (more variables), the harder it is to match fields.

[spencer046]

@pedrodrfaria No I want see to see if for below dataset, I can have one name (let's say MIELE) instead of the 5 different names (BAY CITIES, DDC, Dependable, Los Angles Service Center) for the city state zip combo (Los Angles_CA_90023)

Los Angeles_CA_90023 BAY CITIES C O BARBARA
Los Angeles_CA_90023 DDC CALIFORNIA
Los Angeles_CA_90023 Dependable Distribution Center
Los Angeles_CA_90023 LOS ANGELES SERVICE CENTER
Los Angeles_CA_90023 MEILE

[pedrodrfaria]

Hi @spencer046 

In your dataset, does the columns for City, State and Zip Code have the possibility of not being written correctly? Because based on the sample you sent, the first solution still meets the criteria you want.

Will assign a unique Name column for all the same City, State and Zip code.

Would this be a solution for your case?

Pedro.

[pedrodrfaria · Accepted solution]

I have attached an example doing the previous way I suggested and also doing fuzzy matching.

Please remember to assign the post a solution so other people can see it as the answer to do Fuzzy Matching doing via Purge Mode.

[spencer046]

@pedrodrfaria That's exactly what I needed and it worked for my dataset perfectly. I was doing Fuzzy match for a while but it never crossed my mind to not use the record ID in the match tool. Thank you so much!