What does it look like to implement dbt at an organization where the number of employees is in the thousands? In this video we'll learn from the people who have answered exactly this question at organizations like JetBlue and Chesapeake Energy.

Speakers: Chris Holliday (Moderator), Senior VP, Client Management with Visual BI Amy Chen, Solutions Architect with Fishtown Analytics Ryan Goltz, Lead Data Strategist with Chesapeake Energy Ben Singleton, Director of Data Science & Analytics with JetBlue

Join us for a fireside chat with members of the Netlify data team to get an inside look at how their team gets work done. We'll learn how their data team is structured, some projects they've recently worked on, and what's coming up for the team!

Featured speakers: Emilie Schario, Senior Engineering Manager, Data and Business Intelligence with Netlify Laurie Voss, Senior Data Analyst with Netlify Francisco Lozano, Senior Analytics Engineer with Netlify Brian de la Motte, Senior Data Engineer with Netlify

Almost all of us are using our data warehouse to power our business intelligence, what if we could use data warehouses do even more?

What if we could use data warehouses to power internal tooling, machine learning, behavioral analytics, or even customer-facing products?

Is this a future we're heading for, and if so, how do we get there?

In this video, you'll join a discussion with speakers: - Boris Jabes, CEO of Census - Jeremy Levy, CEO of Indicative - Arjun Narayan, CEO of Materialize - Jennifer Li, Partner at a16z as moderator

Learn more about the speakers and their companies at: https://www.getcensus.com/ https://www.indicative.com/ https://materialize.com/ https://a16z.com/

Learn more about dbt at: https://getdbt.com https://twitter.com/getdbt

Learn more about Fishtown Analytics at: https://fishtownanalytics.com https://twitter.com/fishtowndata https://www.linkedin.com/company/fishtown-analytics/

You’re in a state of flow, building out dbt models and then you get the dreaded message — "Quick question about this data..."

As a data team, how do you balance the roadmap work against those "quick" questions?

How do you prioritize all the work you need to do in the short-term (backlog items) while also working on your long-term projects (roadmap items)?

There are advantages to both backlog and roadmap items. How can data teams get the advantages of both?

In this video, Jacob Frackson will show how Data Clinics dedicated time put aside to work on these requests, can help your data team achieve this balance and empower self-serve along the way.

Data clinics have helped an organization: - Deliver 80% of Sprint Points - Answer up to 8 data questions per day - 10x weekly self-serve users on BI tools

Learn more about dbt at: https://getdbt.com https://twitter.com/getdbt

Learn more about Fishtown Analytics at: https://fishtownanalytics.com https://twitter.com/fishtowndata https://www.linkedin.com/company/fishtown-analytics/