A Devops Approach to Data: A Tale Through the Trenches in Search of a Cloud Data Revolution
summary
Real examples and tools: a team migrates eight on‑premise SQL Server instances to Snowflake, uses Terraform provider for Snowflake + AWS S3, Jenkins or GitHub Actions for CI/CD, and dbt for the data model. Practices include automated dev/staging environments, monitoring and alerting, infra as code, and training analysts to self‑serve. Metrics and outcomes matter: a 60/4/20 org chart, reusable pipeline modules, and zero to repeatable automated analytics within a week.
AI-written summary · about
chapters (6)
- 0:00Intro
- 5:25Where had we got to
- 6:40How can we do better
- 9:52Good software platform engineer practices
- 13:38Relational databases
- 22:48Summary
related talks
30mDevOps For Data Teams
28mDevOps in a Data Warehouse: Inside Out
28mUsing Dataops To Build And Manage Data Products On Snowflake
26mDevOps in a Data Warehouse: Inside Out
23mBridging the DevOps Gap in Modern Data Teams
29mMaking tech boring to keep data exciting
51mFrom DevOps for data to DataOps
27mHow To Develop & Operate An Agile Cloud Datawarehouse In A Rapidly Changing Multi-ERP Environment