Fuzzy matching is used in situations in which the client needs to develop data-driven insights off of disparate data sources in which there are missing keys, messy data and/or unstructued data.

1. Customer Insight (golden record or single source of truth)
2. Employee records, including skills & capabilities
3. Longitudinal pation record
4. Other master data management applications

Given the pervasiveness of these use cases that we have seen with our customers, we want to provide shared best practices and IP around fuzzy matching.

See the deck Introduction to Fuzzy Matching Standard Delivery IP found in the docs folder

The docs contains best practices and resources for implementing fuzzy matching solutions. The docs are broken down into the following sections:

• Data Management
• People Matching
• Knowledge Graphs

├───architecture
├───data
├───docs
├───notebooks

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