All speakers

Mike Driscoll

Co-Founder & CTO, Rill Data

Mike has spent over two decades as a technologist, entrepreneur, and investor. He’s currently co-founder and CEO of Rill, a cloud service for operational intelligence. Previously he founded Metamarkets (acquired by Snap, Inc. in 2017), a real-time analytics platform for digital ad firms, and CustomInk.com a leader in custom apparel online. Mike was also a founding partner at the venture capital firm DCVC, which has invested over $2B+ in assets in deep tech. He began his career as a software engineer for the Human Genome Project and later received a Ph.D. in computational biology.

Mike Driscoll

Sessions / 2025 / 1 talk

  • A SQL-Based Metrics Layer for DuckDB and Clickhouse

    The ability to aggregate raw data into summarized metrics and slice them across dimensions is at the core of analytics teams' work. This session reveals how Rill has developed a metrics layer that declares metrics entirely with SQL expressions, overcoming traditional limitations of metrics management. By leveraging DuckDB and Clickhouse, attendees will discover how to generate multi-dimensional OLAP cubes, implement real-time data access with sub-second performance, and create uniform dashboards through a BI-as-code philosophy. Learn how to define, manage, and secure metrics using an innovative SQL-based approach that transforms raw data into powerful, actionable insights.

Sessions / 2017 / 1 talk

  • The Right Stuff: Lessons Learned from a Decade of Data Engineering

    With more than a decade of Big Data experience now behind us, we’ll talk with a few veterans from the front lines about what skills mattered — and what didn't — on the first data engineering teams at Silicon Valley’s data-intensive start-ups. This will be a must-watch panel for those looking to build out a data-engineering function or get into the field themselves. We’ll explore the build vs. buy debate, looking at which classes of software teams hand-rolled, borrowed (and extended) from open-source projects, or bought - and discuss how that mix is changing. We’ll learn about the hardest parts of data pipelines and the data stack to build. And we’ll highlight the necessary skills that make data engineers different than data scientists.

Ready to take this stage?

The next edition is programmed by practitioners. Tell us what you built and what you learned.

Apply to be a speaker