The Architecture of a Scalable Data Science Platform
summary
Description of an open-source architecture built to power IBM Data Science Experience, delivering full Jupyter notebook sessions in the browser while keeping compute and data on a scalable, secure enterprise cloud. The talk explains the technologies used (Jupyter notebooks, IBM cloud platform components, and related open-source projects like Apache Spark/SystemML/Bahir/Toree) and how the platform enables scalable, secure data-science workflows.
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chapters (7)
- 0:00Introduction
- 3:01Jupyter Notebook challenges
- 6:55Enterprise Gateway solution
- 10:26Key features and security
- 12:35Architecture overview
- 15:02Resources and next steps
- 16:33Q&A
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