Innovating with Data
summary
Three business models are defined: data as a competitive advantage, data as a product, or data that merely improves existing offerings; companies like GE buy billion‑dollar software to capture that value. Practical pipeline is to harvest and harmonize sources, apply cataloging and master‑data discipline, then run AI/ML on cloud platforms using data virtualization and an “answer fabric” for inference. Examples: soil sensors raise potato yields, IoT enables dynamic auto insurance pricing, Experian‑style scoring finds ~60M upsellable customers from a 300M base. 1% improvement translates to millions.
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chapters (8)
- 0:00Introduction and personal journey
- 4:18Why innovate with data
- 10:05Three waves of innovation
- 15:09Data as business leverage
- 21:16From reporting to predictive analytics
- 25:33Data science and citizen roles
- 33:06Real-world data innovation examples
- 43:21Key takeaways and conclusion
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