Fireside Chat: Building The Lakehouse
summary
Two UK businesses describe concrete outcomes: replatforming on Databricks, building a functional data mesh, and scaling a team from roughly five to ~60 people with a 10-person graduate pipeline. Marketing activation time drops from three months to three minutes; clinicians spot a ~66% referral drop during lockdown and use reports to prevent thousands of cases of sight loss. Maturity sits around 2/10, goals target automation, ML ethics, and embedding data invisibly into products.
AI-written summary · about
chapters (8)
- 0:00Introduction and welcome
- 1:48ITV and Specsavers strategies
- 7:09Data maturity journeys
- 13:15Real-world data use cases
- 19:37Hiring and growing data teams
- 27:30Future roadmap and next steps
- 31:07Audience Q&A session
- 44:16Closing remarks
related talks
28mScaling the Future: Lakehouse Architecture and OpenSource Collaboration
20m3-phased approach to delivering a lakehouse with data mesh
33mPanel discussion - Melbourne
41mOn Data: Sky above, sand below, peace within
35mBuilding Data-Intensive Teams
54mBehind the Hype - Architecture Trends in Data
20mKeynote Review
49mPanel discussion - Building Data Products
