We’re on a mission to elevate the analytics profession.

We believe that data analysts are the most valuable employees of modern, data-driven businesses. We build tools that empower analysts to own the entire analytics engineering workflow.

By Analysts, for Analysts

dbt is built and maintained by Fishtown Analytics. In addition to building dbt, we also provide a range of professional services including dbt implementation, strategy, and support.

💡 Imagined by analysts

dbt arose from a simple need: building cascading views on top of email marketing data in Redshift. Fishtown Analytics Founder, Tristan Handy, had been an analyst for 20 years, but those early versions of dbt made him feel like a superhero. He wants every analyst to experience that.

🔬 Tested by analysts

Every analyst at Fishtown Analytics is a dbt power user. We’ve implemented dbt at 100+ companies and our analysts help set our product roadmap, vet every new feature, and apply it to our clients’ projects – only then do we roll updates out to the entire community.

🚀 Empowering analysts

We believe that analytics is a trade. From dbt Slack to Meetups, dbt Learn to our blog, we’re not here to just build technology: we want to empower analysts to have more fulfilling, impactful careers by elevating how the analytics trade is conceived of and practiced.

The dbt Viewpoint

We believe that data analysts should work more like software engineers. In doing so, they unlock their own creative potential and dramatically expand their impact on their organizations. We call this analytics engineering.

1. Analytics is collaborative.

We believe that mature analytics workflows should have the same features that have made software engineering teams successful collaborators: version control, quality assurance, documentation, and modularity.

2. Analytic code is an asset.

The code, processes, and tooling required to produce analysis are core organizational investments. We believe a mature analytics workflow should have the following characteristics so as to protect and grow that investment: environments, service level agreements, a design for maintainability.

3. Analytics workflows require automated tools.

Analysts spend an enormous portion of their time on repetitive, mundane tasks. We believe analysts’ tooling should automate these processes in the same way software engineers’ tools do today. Data ingestion, testing, modeling, and documentation should all leverage automation to a much greater degree than they do today.

Read the complete dbt viewpoint here

Join us 👋

We're working together to level up the analytics profession by applying software engineering best practices to analytics. If that mission feels exciting to you, maybe you should join us.