dbt Labs

Your dbt State questions probably don’t fit neatly into a demo. So we’re keeping the refresher short and leaving more time for your questions. Join the PMs and engineers building dbt State for 30 minutes of open Q&A on your architecture, edge cases, and “will this work for my setup?” scenarios. Bring your questions. Get direct answers. 🛠️ Register now: https://bit.ly/46N6BWr

Whether you were with us in Las Vegas or tuned in virtually, thank you for making #dbtSummit what it was! The best part of Summit is always the people, and the good news is you don't have to wait a year to get together with the community again. We've got 11 in-person dbt Meetups coming up in October 🙌 🇩🇪 Northern Germany (Hanover) | October 10th | Organized by Jannes Walter, Daniel Gleiniger and Angelina Aschemann 🇪🇸 Barcelona | October 8th | Organized by Ruth Onyekwe, Carolina Battaglia, and Uchechukwu Njoku, PhD 🇨🇦 Montréal | October 8th | Organized by João Vitor de Camargo, Romain LOPEZ, and Henri Trouillard 🇳🇱 Netherlands | October 13th | Organized by Thomas in't Veld and Juan Manuel Perafan 🇺🇸 Atlanta | October 20th | Organized by Zoe Yim 🇫🇮 Helsinki | October 20th | Organized by Romulo Carvalho, Tuula Alanen, and Janne Sipilä 🇦🇹 Vienna | October 20th | Organized by Johannes Schauer 🇩🇰 Copenhagen | October 21st | Organized by Anders Boje Hertz, Marie Henkelmann, Marie Adelgaard Lunde, and Kathrine Sofie Rasmussen 🇨🇦 Vancouver | October 21st | Organized by Oleg Agapov, Marcus Wong, and Matt Helm 🇬🇧 London | October 21st | Organized by Edward Hayter and James Charnley 🇹🇼 Taipei | August 26th | Organized by Karen Hsieh, Laurence Chen, Allen Wang, and LI KUAN LIAO We're also looking for Meetup co-organizers for the following locations 👇 Americas: San Francisco, Los Angeles, Portland, Seattle, Austin, Atlanta, Philadelphia, Boston, Washington DC, Bogotá EMEA: Dublin, Munich, Vienna, Bratislava, Prague, Stockholm, Rhein-Ruhr, Belgium APAC: Tokyo, Bangalore, Sydney, Brisbane, Melbourne, Wellington Interested? Raise your hand here: https://lnkd.in/gpqbXefz dbt Meetups are gatherings dedicated to helping you own your analytics engineering workflow. If you don’t see a meetup near you, find your local dbt chapter and join the group to get notified about future events https://lnkd.in/ekknesFN

We brought Explore mode for dbt Wizard to Public Preview at #dbtSummit last week. Now it's time to get hands-on. Explore mode gives business users a new way to answer questions about production data, using the context your data team has already built in dbt. Ask “What was total revenue in Q2, by month?” and explore the results in a chart or table. When you need a closer look, your data team can inspect the SQL or governed metric behind the answer in the same platform, making it easier to validate results together. Explore independently. Validate together. All without changing your dbt project. Bring your next business question to dbt Wizard. Try Explore mode: https://bit.ly/4e4dir0

92% of companies plan to increase AI investment over the next three years. 1% of leaders call their organization mature in AI deployment. That gap is a data problem. Most AI maturity models measure adoption: strategy, use cases, workforce readiness. None of them tell you whether your data foundation can actually support AI and agents in production. The Enterprise AI Data Maturity Model measures the part that decides it. Two phases, five stages, and six dimensions: data quality, governance, ownership, cost, context, and interoperability. Start with the honest answer to one question: can anyone trust the data today. Find your stage: https://bit.ly/3VjEHPl

Agents don’t make bad data foundations better. They amplify them. On September 30 at 12 p.m. ET, Tristan Handy, President and Co-founder of Fivetran + dbt Labs, joins Juan Sequeda and Tim Gasper on Catalog & Cocktails Honest No-BS Data Podcast to talk about what changes when agents become primary consumers of enterprise data. Expect a conversation on open infrastructure, trusted context, and why the fundamentals of analytics engineering matter even more in an agentic world. 📺 Join us live on LinkedIn https://lnkd.in/e84yiqke

Your warehouse is great at warehouse workloads. That doesn’t mean every dbt model needs to run there. In our upcoming live demo, we’ll take a DAG from all-Snowflake → Iceberg-powered sources → Lake Compute, showing how to choose compute model by model. Store once. Compute where it makes sense. Pay warehouse prices only for the work that needs it. See it live https://bit.ly/4d6I1U6

AI agents are fundamentally changing who consumes data -- and at what scale. Tristan Handy spoke with CRN about what that means for the infrastructure underneath it: open, integrated building blocks that treat agents as first-class users. The piece digs into several major announcements from #dbtSummit, including dbt v2, dbt State, and Fivetran Context Layer -- and Shawn Toldo, VP of Worldwide Partner Ecosystem, shares how Fivetran + dbt Labs are bringing the platform and partner ecosystem together for what comes next. Good read on where we’re headed and how partners like Brooklyn Data (Velir's data studio) are thinking about the AI-driven opportunities ahead. https://bit.ly/4dNkoA0

Four days. A lot happened. We shipped dbt v2. Introduced dbt State, Wizard, Lake Compute, and Charts. Built things in workshops and broke things in the hackathon. Talked agents, context, Iceberg, analytics engineering, and what comes after the modern data stack. But #dbtSummit has never really been about the agenda. It’s the hallway conversations. Meeting the person behind the Slack handle. Comparing notes on the problem you thought only your team had. Helping someone debug something. Leaving with three new ideas you’re already thinking about implementing on Monday. Ten years into dbt, this community is still figuring out what comes next together. Thanks for leveling up with us in Vegas. Now go build something. 🧡

Enough slides. Time to build. At today’s #dbtSummit Data + AI Agent Hackathon, practitioners got hands-on with MCP, agent skills, and dbt to experiment, iterate, debug, and ship working data agents in a single sitting. Some were building their first agent. Others were testing the edges of what’s possible. Either way, code was written. Things broke. Things shipped. 🤖

Build what changed. Skip what didn’t. Do it faster. We caught up with a #dbtSummit attendee after the keynote, and dbt State + Fusion were top of mind. Here’s why they’re excited to get their hands on them. 🎤👇