Using Fuzzy Lookup and Grouping in SSIS

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Want to build a reliable, modern data architecture without the mess?

The Fuzzy Lookup transformation performs data cleaning tasks such as standardizing data, correcting data, and providing missing values.

The Fuzzy Lookup transformation differs from the Lookup transformation in its use of fuzzy matching. The Lookup transformation uses an equi-join to locate matching records in the reference table. It returns records with at least one matching record, and returns records with no matching records. In contrast, the Fuzzy Lookup transformation uses fuzzy matching to return one or more close matches in the reference
table.

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The Fuzzy Grouping transformation performs data cleaning tasks by identifying rows of data that are likely to be duplicates and selecting a canonical row of data to use in standardizing the data.

The Fuzzy Grouping transformation requires a connection to an instance of SQL Server to create the temporary SQL Server tables that the transformation algorithm requires to do its work. The connection must resolve to a user who has permission to create tables in the database.

Timestamps:
0:00 - Intro
0:05 Demo Background
0:32 Implement Fuzzy Lookup
4:23 Implement Fuzzy Grouping
7:23 Closing

Title & Tags:
Using Fuzzy Lookup and Fuzzy Grouping in SSIS | SQL Server Integration Services (SSIS) Tutorial
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