Dec 2020

Product Spotlight: Matchmaker

Even before Purpose Analytics started, we heard from multi-service agencies that they were burdened with collecting data in multiple systems. While it is tempting to look for a single system that does it all, doing so is like hoping that a Swiss Army knife can replace all the implements in your kitchen. It may be possible, but it doesn't lead to good results.

Nevertheless, keeping data in multiple systems can make analysis challenging, especially when information about service users is split across more than one database.

Matchmaker solves this problem by providing you with a master index and linkage table that can be used to connect records between datasets. Built by Purpose Analytics using DataMade's excellent dedupe Python library, Matchmaker employs fuzzy matching to find individuals that appear in multiple databases.

This can be a starting point for your analysis, including:

  • determining the number of unique individuals served by your organization
  • understanding the flow and progression of individuals through your programs
  • automating the migration of records between databases.

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