Manage data as a strategic asset. Implement data lineage, catalogs, and automated quality frameworks to ensure trust and compliance.
Bad data leads to bad decisions. This course focuses on the 'managerial' side of data engineering: Governance. You will learn to implement Data Catalogs to make data discoverable, track Data Lineage to understand dependencies, and enforce Data Quality using automated testing frameworks like Great Expectations. We cover Master Data Management (MDM), compliance (GDPR/CCPA) in engineering, and how to build a culture of data stewardship within an organization.
Estimated completion time: 21 lessons • Self-paced learning • Lifetime access
It is critical infrastructure work for enterprise success.
Yes, specifically Python for quality testing frameworks.
Banks, Healthcare, and large Tech companies.
We use open-source tools like Great Expectations.
3 recommended paths based on what you're learning
Go beyond the basics. AI Engineering Leadership builds directly on what you know.
While everyone focuses on Data Governance & Quality, the smart ones are also learning Causal Inference.
The smartest Data Governance & Quality professionals are using Hugging Face AutoTrain to fine-tune models without writing code.