What you'll learn

Unmanaged changes to pipelines, schemas, and analytic assets create silent failures, broken dashboards, and unpredictable data behavior across environments.

In this course, DataOps Foundations: Versioning and Change Management, you’ll gain the ability to apply disciplined versioning and change management practices that make data systems transparent, reproducible, and safe to evolve.

First, you’ll explore how version control supports collaboration, traceability, and reproducibility across code, configurations, schemas, and data artifacts.

Next, you’ll discover how branching, merging, tagging, and metadata-driven lineage enable controlled evolution and reduce risk during iteration and experimentation.

Finally, you’ll learn how to apply change management practices including release workflows, schema evolution strategies, CI/CD quality gates, and rollback techniques to deploy data changes safely and predictably.

When you’re finished with this course, you’ll have the skills and knowledge of DataOps versioning and change management needed to deliver reliable, auditable, and confidently evolving data pipelines.