Jamie Davidson

Self-service has been promised before. Every BI vendor put it on their front page a decade ago, most data leaders tried it, and the ticket queue never went away. The skepticism is earned. The usual diagnosis is that the tools weren’t good enough. But something subtler is going on. There’s always a gap between what someone asks for and what they actually need. By the time a request lands in your queue, it’s already been compressed: a problem someone lives with daily, translated into a shape they think a data team can service. Good analysts close that gap. They just have to do it one ticket at a time. Synthesia’s Gina Jenks joins Omni co-founder Jamie Davidson to talk about what happened when Synthesia stopped closing that gap ticket by ticket. What they built, which of the usual blockers turned out not to matter, and what people made once they didn’t have to ask first.

Analytics engineers built transformations to define metrics and share them in the data warehouse. But AI agents need more than definitions. They need context. At Checkr, the analytics engineering team treats context engineering as the next evolution of their practice. This session covers what it looks like to engineer context, organizational knowledge and governance into AI systems — including what semantic layers usually miss; how to accelerate with LLM-assisted tooling; how to build a feedback loop that makes AI smarter over time; and why this discipline is becoming the core of the analytics engineering role, not a side project.

Stuck on a treadmill of endless data requests? Omni and Snowflake Cortex let your users answer their own questions with a little help from AI. No magic, no miracles — just smart tooling that gets the semantics right to deliver clear, actionable insights. This talk will provide a blueprint for keeping pace with AI while freeing up your team to focus on what really matters.