Data Quality Testing with Great Expectations
With Sam Bail
Liked by 2 users
Duration: 1h 34m
Skill level: Intermediate
Released: 4/16/2026
Course details
Data quality is the foundation of reliable analytics and machine learning—even the most advanced analytics platform or AI model is worthless without accurate, trustworthy data. In this course, expert data engineer Sam Bail teaches you how to use Great Expectations, a powerful open-source framework for testing and validating data. Explore when and where data quality testing matters most, and find out how to configure both the open-source and cloud-based versions of Great Expectations for your workflows. Leverage hands-on examples to implement data quality tests, interpret the results, and debug common issues. This course equips you to build robust, trustworthy data pipelines that catch data problems before they cause downstream damage.
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