dbt defined an entire new subspecialty of software engineering: Analytics Engineering. But it is one discipline among many: analytics engineers must collaborate with data scientists, data engineers, and data platform engineers to deliver a cohesive data platform. In this video, Nick Schrock of Elementl talks about how orchestrating dbt with Dagster allows you to place dbt in context, de-silo your operational systems, improve monitoring, and enable self-service operations.

Using dbt's metadata on dbt runs (run_results.json) Drizly analytics is able to track, monitor, and alert on its dbt models using Looker to visualize the data. In this video, Emily Hawkins covers how Drizly did this before, using dbt macros and inserts, and how the process was improved using run_results.json in conjunction with Dagster (and teamwork with Fishtown Analytics!)