Release Management For Data Platform Services And Logic

This podcast episode explores the challenges of testing data pipelines and managing releases, particularly in relation to maintaining data connections, validating transformations, and ensuring a reliable Quality Assurance (QA) process. It discusses the difficulties of working with production data in a pre-production environment and the importance of testing transformations against a realistic target with production data. The section also highlights the tight coupling between dbt code and Dagster pipelines and the need to break that coupling for more efficient deployment. The episode addresses the challenges of accessing QA environments, managing code bases and resource definitions, and validating data sets before publishing changes to production. It concludes by emphasizing the importance of investing in data versioning capabilities and encouraging collaboration and sharing experiences in release management.