We are celebrating the 10-year anniversary of the Alteryx Community! Learn more and join in on the fun here.
Start Free Trial

Alteryx Designer Desktop Discussions

Find answers, ask questions, and share expertise about Alteryx Designer Desktop and Intelligence Suite.

Comparing dataset for matches with High similarity score for name field.

Harsha09
5 - Atom

Can Alteryx compare data sets where, there is a mismatch between some names like 

1. Accenture PLC or Accenture Public Limited Company 

2. SG Fund  or   Son Gate Funds.

3 REPLIES 3
caltang
17 - Castor
17 - Castor

That's a very big mismatch.... if you're talking about similarity rates and checking, then you can use Fuzzy Matching on that.

 

But if you're talking pure matching with two data sets, then you can try with a a Join tool to see what matches in J, and what doesn't in R / L.

Calvin Tang
Alteryx ACE
https://www.linkedin.com/in/calvintangkw/
Hammad_Rashid
11 - Bolide

Yes, Alteryx Designer can be used to compare datasets for matches with high similarity scores for fields like names, even when there are variations or mismatches in the names. Alteryx provides a variety of tools and functionalities that can help in data preparation, cleansing, and matching.

 

To compare names with high similarity scores, you can use tools like:

  1. Fuzzy Match Tool: This tool allows you to compare and match strings based on their similarity. It considers variations in spelling, typos, and other discrepancies. You can adjust the similarity threshold to capture matches with high similarity scores.

  2. Join Tool with Fuzzy Matching: You can use the Join tool and configure it to perform a fuzzy match on the name field. This way, you can join records that have similar names even if they are not exact matches.

Here's a basic outline of the steps you might follow:

  1. Input Data: Bring in your datasets into Alteryx.

  2. Data Cleansing: Cleanse the name fields to standardize the format (e.g., removing extra spaces, converting to uppercase).

  3. Fuzzy Matching: Use the Fuzzy Match Tool or configure the Join tool to perform a fuzzy match on the name field. Adjust the similarity threshold to capture matches with high similarity scores.

  4. Output: Review the output to identify matched records and explore the similarity scores.

Keep in mind that the effectiveness of fuzzy matching depends on the specific use case and the nature of your data. You may need to experiment with different settings and tools to achieve the desired results.

 

inyang
5 - Atom

Hi Hammad,

I like your answer and would like to have workflow that illustrates this steps . I am trying to compare dataset for various data sources for a match with high similarity score for specific named field.

Labels
Top Solution Authors