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Platform Product: Fuzzy Matching Issues – Working with Alteryx Customer Support Engineers
(for use by CSEs and Alteryx Customers)
To EXPEDITE the resolution of your case, please include the below information.
Fuzzy Matching- Requested Information
*** Suggestion: copy/paste the questions below and email the supporting documentation to email@example.com
1. Detailed Description of the Issue
2. Screenshot of Alteryx Version
3. Screenshot of Error
4. What dataset and vintage are you using?
5. Please send a copy of your workflow (*.yxmd or *.yxzp) and sample data if possible.
Fuzzy Matching – Requested Information (Detailed Instructions):
1. Detailed Description of the Issue – What issues are you having? Has it worked in the past? When did the issue start? Are all users affected or just some? What are the steps to reproduce your issue? What have you tried to resolve the issue? Have you searched the Alteryx Community using the Fuzzy Match label?
2. Screenshot of Alteryx Version– Our CSEs need to know the precise version of Alteryx so we can replicate any issues. In Alteryx, click Help >> About and provide a screenshot.
The screenshot will include whether it is Server or Designer. In addition, whether it is “Running Elevated” Admin vs. Non-Admin.
3. Screenshot of Error or Exact Text of Error- Click CTRL-Print-screen to capture the error and paste into your e-mail. Also include where was the error encountered – Gallery, Designer, Scheduler?
Note: You may wish to Google the error text research the issue. The Knowledgebase is also a great place to search the error text as well!
4. What dataset and vintage are you using? From the Allocate Input tool, click the drop down for Choose a Dataset. What dataset is selected? If “Most Recent Vintage,” what is the dataset below? e.g. Experian US 2018A (Q4 2018)
5. Please send a copy of your workflow (*.yxmd or *.yxzp) and sample data if possible. Either create a .yxzp and include macros and data by clicking Options>Export Workflow. Or, include the workflow *.yxmd and sample data if possible.
Tool Mastery | Fuzzy Match
Keyword Fuzzy Matching Strings: Clean Human Entered Data
Tips and Tricks for Fuzzy Matching
The Fuzzy Match Tool has the ability to match first names against a set of Nicknames to help return better matches. The Nickname table (which can be found at C:\Program Files\Alteryx\bin\RuntimeData\FuzzyMatch\Nicknames) is used as a lookup within the Fuzzy Match tool when you select it as an option. Selecting “Name w/ Nickname” as your Match Style automatically selects the Common Nicknames table, but often users would like to add to this list or even create their own custom table. This article will walk you through how to edit this list, and provide you with some tips and tricks when matching with nicknames.
Creating a Nickname table
The nickname table is installed by default in C:\Program Files\Alteryx\bin\RuntimeData\FuzzyMatch\Nicknames and is saved as an Alteryx database file (.yxmd). We can easily pull this into Alteryx to add additional names, or we can even generate our own table. The .yxdb file contains 2 fields:
Full Name goes here
Nickname goes here
Adding Additional Names: Creating your own file: Once the file is created, place the .yxmd in the directory above. You should now be able to see multiple tables available from the dropdown within the tool.:
Tips and Tricks when working with Nicknames
Set Generate Keys to “None” when using the Names w/ Nicknames match style IF you have the First Name in a single field.
If your name is contained in a single field (John Smith or Smith, John), you will want to select a method to Generate Keys and check the box “Generate Keys for Each Word”.
The “Soundex” method of generating keys is generally preferred when working with names.
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.