All speakers

Benn Stancil

Founder, Mode

Benn Stancil is a cofounder of Mode, an analytics and BI company that was bought by ThoughtSpot in 2023. While at Mode, Benn held roles leading Mode’s data, product, marketing, and executive teams; at ThoughtSpot, he was the Field CTO. More recently, Benn worked on the analytics team on the Harris for President campaign. He regularly writes about data and technology at benn.substack.com.

Benn Stancil

Sessions / 2026 / 1 talk

  • Benchmarking AI Agents Against Realistic Analytical Tasks with ADE-bench

    There are many benchmarks that attempt to measure how well LLMs and AI agents can write SQL queries or do complicated statistical analysis. But as most practitioners know, this is only a small part of our job. Before we can write a query, we have to figure out the business context behind the question. We have figure out which tables to use in a messy database. We have to make subjective decisions about vaguely defined problems. All of this makes benchmarking analytical agents difficult. We built a new benchmark—ADE-bench—that aspires to do exactly that. It gives agents complex analytical environments to work in and ambiguous tasks to solve, and measures how well they perform. In this talk, we'll share how we built the benchmark, the results of our tests, a bunch of things we learned along the way, and what we think is coming next. The benchmark harness is open source, and can be found here: https://github.com/dbt-labs/ade-bench

Sessions / 2024 / 1 talk

  • WTF Are We Doing?

    The volume of data-focused communities has exploded over the past couple of years, along with a never-ending stream of think pieces on building a data culture. With so much buzz, we gotta ask: are we truly making strides toward building a more effective data industry, or are we merely swept up in the hype? Are our efforts yielding tangible results, and are they worth the investment? Join us as our panel of industry experts share their unfiltered perspectives across a few targeted areas: What's the impact of rapidly proliferating data communities on the broader industry? What are we getting right, and where are we fundamentally failing? With rapid advancements in AI and data tooling, are we actually closer to having well-functioning and impactful data teams? Have we adequately addressed the underlying people/process problems that generally fall under the ""data culture"" umbrella? How and why do companies and communities continue to fail to rally around data despite myriad tooling options and endless think-pieces about what it takes to get it right?

Sessions / 2022 / 1 talk

  • The Return of the OLAP Cube

    Fifteen years ago, OLAP cubes were a critical part of every analytics and BI stack. In a time when databases were slow and compute was expensive, cubes provided an elegant solution for standardizing multi-dimensional reporting. Over the last decade, however, they’ve fallen out of favor. As warehouses have gotten bigger, faster, and cheaper, cubes no seem longer necessary. Analysis and reporting is now done directly on top of raw data, no predefined or pre-aggregated cubes required. Or are they? OLAP cubes are reappearing in the modern data stack—just in a different form and under a different name. Instead of being separate data marts built for reporting and BI, cubes are now synthetic, generalized, and on-demand. In this talk, I’ll walk through the history of OLAP cubes and their modern echoes. And I’ll explain why this is actually a good thing—and why we should actually be excited about the return of the OLAP cube.

Sessions / 2019 / 1 talk

  • Building an End-to-End Data Stack in Thirty Minutes

    Data stacks - from launching data collection pipelines, provisioning data warehouses, developing ETL systems, and integrating data science and BI applications - used to take teams weeks and months to build. Today, using off-the-shelf tools, companies can set up this entire infrastructure in a matter of hours, all without needing specialist data engineers. This talk will not only introduce the technology that makes this possible - it will also show how it can be done, in a live demo. During this talk, Benn will set up an end-to-end data stack, highlighting how any company can go from having little than a website to running automatic data pipelines, a scalable data warehouse, live dashboards, and a data science platform in under thirty minutes.

Sessions / 2018 / 1 talk

  • Building Data Tools that Work

    We work with hundreds of companies who are building tools to help them get value of their data. The most important predictor of their success is rarely the technology they choose to use, but the way they choose to use it. Consistently, successful companies focus on helping people rapidly answer questions that constantly evolve, while companies that fail tend to focus on data over people, technology over business needs, and the current world over where the world might be. I'll survey how we've seen leading data companies apply this approach to different technologies companies - and why other companies have tried to use the same technologies and failed.

Sessions / 2017 / 1 talk

  • Data for the 99%

    Leading tech companies like Facebook and Airbnb are building tools to solve problems at the bleeding edge of the data ecosystem. The complexity and scale of these problems are not typical, even at most tech companies. The vast majority struggle with far more fundamental challenges around logging, processing, moving, and analyzing data. This talk will outline the the problems this "silent majority" of tech companies face, and survey how a new stack of data tools is helping them quickly build impressive data infrastructures from the ground up.

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