Yes, but it takes some wrangling. Unlike Alteryx, there is no “fuzzy match” tool in Tableau Prep, but there is a method you can employ which will help (though, like all fuzzy matching, it isn’t perfect).
Imagine we have customer data from two different databases that we are trying to merge. The customer names are often the same, but not always.
Here are the company names from Database A:
Here are the company names from Database B (different names enclosed):
We want all the company names from Database B to reflect how they are spelled in Database A so that when we combine data from the two databases, the Company Name field contains clean matches.
This is a perfect opportunity to use Tableau Prep’s “Group by Pronunciation” feature. In Tableau Prep’s automatic grouping, multiple values may match to create a single value. When this occurs, that grouped value is named after the value that had the most records in the data.
Since we want the group names to reflect the company names from Database A, we will perform a multi-table union with the A table twice and the B table once.
Since the company name fields are different in each database, we’ll want to make sure those fields are merged. I’ve renamed the merge field “Company Name - All”.
From there I create a calculated field called “Company Name - Final” which is essentially just a copy of the field “Company Name - All”.
I then performed a Group and Replace by pronunciation on the “Company Name - Final” field which resolves the majority of minor spelling and punctuation differences.
While effective, Group and Replace by Pronunciation isn’t perfect. A few instances still need to be addressed by hand.
From there you would join the original table from Database B to the grouped output. By joining “Company Name - B” to “Company Name - All”, you can see that the company Bartell became Bartell Inc in the final company name field.
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