Great Expectations
Definition
Great Expectations tests data with formulated expectations and makes validation results transparent.
Great Expectations provides GX Core, a Python library for data testing. An Expectation is a verifiable statement about data. Multiple expectations can be bundled and validated against a selected dataset.
Simply explained
Imagine a checklist for a goods delivery. Instead of boxes, GX Core checks data. However, the list only knows the rules previously defined.
Why it matters in practice
Recurring data checks require explicit expectations. This makes it visible whether a data delivery meets the agreed conditions.
Example from business
Possible example: A retailer checks before a report whether the expected mandatory values are present in the imported table.
Limits and pitfalls
- A passed test only covers the formulated expectations. Too narrow or inappropriate rules can reject usable data or overlook important errors.
Origin & history
The read documentation of version 1.24.0 describes the process from data connection through Expectations to validation. It does not specify a confirmed project inception year.
Use in mid-sized companies
- A validation stage between data import and monthly evaluation is conceivable. Domain experts should co-develop the expectations and assess error messages.
Frequently asked questions
What is an Expectation?
A verifiable statement about the data.
What do Data Docs show?
A readable presentation of the expectations and validation results.
Sources
- GX Core overview · Great Expectations (o. J.): GX Core overview
Editorially reviewed on: