A framework for orchestrating and comparing data linking and deduplication methodologies.
Project description
Record matching is a chore. 🔥Matchbox is a match pipeline orchestration tool that aims to:
- Make matching an iterative, collaborative, measurable problem
- Compose sources, dedupers and linkers and make the results very easy to query
- Allow organisations to know they have matching records without having to share the data
- Allow matching pipelines to run iteratively
- Support batch and real-time matching
Matchbox doesn't store raw data, instead indexing the data in your warehouse and leaving permissioning at the level of the user, service or pipeline.
To get started, read our full documentation.
Installation
To install the matchbox client:
pip install "matchbox-db"
To install the full package, including the server features:
pip install "matchbox-db[server]"
To run the server, see the server installation documentation.
Use cases
Data architects and engineers
- Reconcile entities across disparate data
- Rationalise about the quality of different entity matching pipelines and serve up the best
- Run matching pipelines without recomputing them every time
- Lay the foundation for the nouns of a semantic layer
Data analysts and scientists
- Use your team's best matching methods when retrieving entities, always
- Measurably improve methodologies when they don't work for you
- When you link new data, allow others to use your work easily and securely
Service owners
- Understand the broader business entities in your service, not just what you have
- Enrich other services with data generated in yours without giving away any permissioning powers
- Empower your users to label matched entities and let other services use that information
Development
See our full development guide and coding standards on our contribution guide.
Project details
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