Great Expectations

Meet Great Expectations

Great Expectations defines data quality through explicit checks called expectations. Engineers use GX Core from environments such as Python and Jupyter to state what a dataset should contain and run validations against it. Those checks give collaborators a shared description of acceptable data.

Data Docs presents results in readable reports and visualizations, letting stakeholders inspect what passed or failed. Orchestration integrations run the checks inside a data pipeline, and configured actions can notify a team or keep failed data from progressing downstream. GX Core is open source under Apache 2.0, so teams can inspect and adapt the framework alongside their own validation logic.