Great Expectations (GX) is the most widely used Python library for data quality validation in pipeline contexts. Its core abstraction is the Expectation — a declarative, testable assertion about data: 'the `runs` column values should be between 0 and 6', 'the `delivery_id` column should have no null values'. Expectations are organised into Expectation Suites validated together against a batch of data. A Checkpoint orchestrates the full validation workflow: load the data, run the suite against it, generate a validation result, and take configured actions based on pass or fail.
GX distinguishes between defining expectations (writing the suite) and validating data (running the checkpoint). Suites are defined once and stored in a configuration directory; checkpoints run the same suite against different batches of data on every pipeline execution. This separation means the quality contract — what the data must look like — is versioned alongside the pipeline code, and every run produces a validation result that documents whether the contract was met. The validation results form an audit trail that answers 'when did this quality issue first appear?'
Analogy🏏Cricket
🏏 Think of it like cricket: Migrating from Airflow to Prefect is like the same bowling coach shifting from traditional Test cricket notation to a modern T20 analytics dashboard — the underlying ball-by-ball data (the business logic) is exactly the same. What changes is how the data is recorded, displayed, and acted upon. The yorker that Bumrah bowls in over 20 is identical whether it is recorded in the old scorebook (Airflow DAG file) or the new analytics platform (Prefect flow). The migration is a transcription exercise, not a strategy change — and a wise coach verifies that the runs, wickets, and economies match exactly between the old and new system before decommissioning the scorebook. That verification step is the whole heart of the migration: because the yorker is unchanged, the only honest test is to run the same over through both systems and confirm the recorded runs, wickets and economies match to the last digit before the old scorebook is thrown away. Rushing to burn the scorebook the moment the shiny dashboard lights up is how teams lose a season of records to a silent transcription slip. The coach keeps both systems running in parallel for a while, reconciles their outputs ball by ball, and only when every figure agrees does he trust the new dashboard alone — a transcription is only complete when you have proven nothing was lost in the copying.
🏏 Showing the Cricket analogy — a Cricket version isn’t available for this concept yet.