DataOps

Principles

1. Continual Customer Satisfaction
2. Value working Analytics: The degree to which analytics are insightful with accurate data, on robust frameworks.
3. Embrace Change - face-to-face interaction with customers.
4. Importance of Teams
5. Daily Interactions
6. Self-organizing Teams are best.
7. No Heroes: Sustainable, scalable teams, processes
8. Self-reflection regularly
9. Analytics is Code
10. Start-to-Finish Orchestration drives success.
11. Reproducibility is Key
12. Disposable Environments
13. Simplicity: Continuous attention to technical excellence and good design; maximize the amount of work not done.
14. Analytics is Manufacturing
15. Quality is Paramount Automated detection of abnormalities, security issues (code, configuration, data); continuous feedback for error avoidance.
16. Quality & Performance Monitoring
17. Reuse Avoid repetition of effort/work
18. Improve Cycle Times Customer needs turned into analytic idea, development, release as reproducible production process, refactor and reuse the product

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