Break Barriers In Real-time With Data Streaming
summary
Shows a deployed Striim pipeline that uses change data capture from a single Oracle reader to feed multiple consumers with isolated checkpoints so one consumer outage doesn’t stall others. Demonstrates streaming SQL continuous queries for real-time models, a real-time Snowflake writer plus 15–30 minute bulk loads for lower-cost tables, replayable persisted logs on Kafka, and schema data contracts that auto-apply safe DDL or alert on breaking changes. Example is a Fortune 500 retail decentralized analytics stack that runs and resumes correctly.
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chapters (9)
- 0:00Introduction and agenda
- 1:25Business intelligence evolution
- 4:54Data as a product concept
- 8:09Real-time data products
- 9:58Decentralized pipelines example
- 13:29Consumer-specific streaming apps
- 18:04Continuous query benefits
- 20:29Data mesh principles
- 22:33Summary and call to action
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