Modernizing the Analytics and Data Science Lifecycle for the Scalable Enterprise: The SEAL Method
summary
Introduces SEAL as a CRISP-DM upgrade that adds SLAs, iterative feedback loops, and continual improvement so models survive enterprise scale and multi‑cloud complexity. Cites a Warner Bros example with billions of views per month, demos cloud migration and operational analytics using MemSQL/Redis, Lambda, AWS/Azure and testing via virtual clones (Delphix). Recommends data virtualization (Denodo/Liftron), automation with DataRobot and Alteryx, and automated drift detection so deployments remain performant, auditable and repeatably maintainable.
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chapters (4)
- 0:00Start
- 16:01Conventional Data Flow -plus Accelerator Patterns and Tools
- 19:00Current Methodologies to Drive Analytics / Data Science Projects
- 29:01Diving Deeper with SEAL: Scalable Enterprise Analytics Lifecycle
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