dbt was open-sourced in 2016, accelerating adoption of the analytics engineering workflow by data teams around the world. In the 6 years since, the community has ballooned to more than 50,000 data practitioners. While many have joined in the last year, a good number of OGs have been around since the very beginning.
If you’re ready to skip past intro chats to dive straight into more complex use cases, tooling, and maybe even touch on the things you realized you could but probably shouldn’t do with dbt… these are the Coalesce replay tracks for you.
Module 1: Getting Better at the Basics (1 hr 50 mins)
You “know enough to be dangerous”—and maybe now you actually are… having picked up a few questionable habits that aren’t scaling as your team expands 😅. These sessions will help you get back on track.
- dbt_project_evaluator (30 mins)
- From worst to first, revamping your dbt project to be world-class (27 mins)
- Breaking Bad (deployment habits) (18 mins)
- But I won’t do that — things you shouldn’t do with dbt (35 mins)
Module 2: One layer deeper (3 hrs 39 mins)
The opposite of “X for dummies.” Because you’re no dummy—you’re a certified badss. You know this stuff. You could teach a course on it. Write a book on it. Do it in your sleep. But just* in case you’re looking for a few extra tips and tricks, these are the sessions for you.
- Workshop: Advanced Testing (46 mins)
- Workshop: Get more out of your DAG (40 mins)
- Workshop: dbt Packages you didn’t know you needed (63 mins)
- Mastering the art of dbt package development (24 mins)
- Automating dbt Development with Pre-Commit (46 mins)
Module 3: New capabilities (2 hrs 40 mins)
Coalesce saw a few new product and feature launches including Python support in dbt, the dbt Semantic Layer. Both are ready for you to start exploring, and these sessions might help expedite that process.
- Hands-on: the dbt Semantic Layer (37 mins)
- Announcing dbt’s Second Language: When and Why We Turn to Python (47 mins)
- Workshop: Build your first dbt Python model (48 mins)
- Empowering pythonistas with dbt and snowpark (28 mins)
Module 4: New Use Cases(2 hrs 30 mins)
You’re ready to start exploring some new ways of work—maybe to be a bit more efficient, or maybe to see how far you can push things without the whole thing falling apart. New features, edge-cases, nearly untested theories, wild ideas—if you want to stay ahead of the curve these sessions are for you.
- Money, Python, and the Holy Grail: Designing Operational Data Models (27 mins)
- Back to the Future: Where Dimensional Modeling Enters the Modern Data Stack (45 mins)
- Build scalable data products leveraging user stitching (31 mins)
- When the Real World Messes with Your Schedule: Event Driven Dbt Models for the MDS (20 mins)
- Standardizing the unstandardized: dbt modeling for Web 3.0 (27 mins)
Module 5: Watch the world burn (2 hrs)
Watching the world burn isn’t a core skill that you should develop… but if you already have it then shoot—welcome to the talks that keep folks talking.
- Data Led is Dumb (21 mins)
- Data teams: kill your service desk (32 mins)
- Babies and bathwater: Is Kimball still relevant? (16 mins)
- Why you should not do lead scoring in your marketing automation tools (25 mins)
- Excel at nothing: How to be an effective generalist (28 mins)
For even more Coalesce talks, be sure to check out the dbt YouTube channel
Last modified on: Nov 14, 2022