About Great Expectations
Great Expectations, also known as GX Core, is an open source framework for testing, validating and documenting data quality. It lets teams state what they expect their data to look like and check it automatically.
What it does
You write expectations, which are rules about a dataset such as a column never being empty or values falling within a range. GX Core runs those checks against your data and produces results that can be rendered as Data Docs. Actions can notify teams or stop bad data from moving downstream, and the checks can be run from an orchestrator on a schedule.
Key features
- Expectations that state rules for each dataset
- Data Docs with plain language test results
- Checks run from orchestrators and automation tools
- Works with Python and Jupyter notebooks
- Actions that notify teams when a check fails
Who it's for
Data engineers, analysts and data quality teams who want shared rules that technical and business people can read. It is a good fit for teams that already work in Python and want checks that live next to their pipeline code.
Pricing and good to know
GX Core is licensed under Apache 2.0 and is free to use. The company says it will always keep GX Core free, and it also sells a separate platform built on the same engine. Writing good expectations takes some thought about what the data should look like, so start with a few important checks and grow the set over time.
Highlights
- Write rules that check each dataset automatically
- Generate readable Data Docs for test results
- Run checks from orchestrators on a schedule
- Use Python and Jupyter notebooks to build checks
- Trigger actions that notify teams when data fails
