You’re sold on dbt, but your org isn’t quite there yet. Whether you’re introducing dbt from scratch or trying to scale it responsibly, this talk is for data practitioners navigating buy-in, timing, and tooling choices. We’ll cover how to choose the right entry point, which features to start with (and which to save for later), and how to align your rollout with your organization’s readiness. You’ll leave with a practical framework for introducing dbt in a way that sticks.

Academia/open science is an as-yet untapped market for analytics engineering, as well as one that could majorly benefit from the tight coupling of data transformation and software engineering best practices. But introducing dbt into this context comes with its own set of challenges. In this session, Šimon Podhajský (iLife Technologies), explains what’s slowing progress here,, and what academics can do to progress this work.

Check the slides here: https://docs.google.com/presentation/d/1aw_cs6V0n-oT9Lp7Vq3MNcRbthEFJEYwcvkCBfuzlR0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.