Scaling Data at Ovoko: The Succesful Strategy
summary
A four to six week Data Operating System discovery produces concrete deliverables: a hiring roadmap (from seven individual contributors to managers and three functions), a reworked stack replacing Redshift with Snowflake on Iceberg, a Looker semantic layer and Mixpanel for product analytics, and an experimentation process. The claim is measurable: a modeled 10% uplift over three years (70:1 ROI), 15 business domains exposed scaling pains, and a running parallel migration that proves usable but brittle while sunsetting the old pipeline; usability and self‑service via self-service via Looker drive the decisions.
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chapters (14)
- 0:00Introduction
- 3:16Data strategy framework
- 8:55Strengths weaknesses gaps
- 13:27Data strategy roadmap
- 15:36Scaling data team
- 19:09Data platform upgrade
- 26:15BI infrastructure choice
- 28:00Product analytics setup
- 35:48Reporting layer KPIs
- 36:30Demand acquisition modeling
- 37:11Tracking experimentation
- 38:15Measuring ROI
- 39:19Acknowledgments
- 39:41Q&A
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