Course prerequisites

This course is geared towards those who have some familiarity with dbt and Dagster. You don't need to be an expert, but you should know your way around a dbt or Dagster project.

  • dbt familiarity

    An understanding of the basics of dbt is required to complete this course. We recommend that you first complete dbt's Fundamentals course if you're a new dbt user.

  • Dagster familiarity

    You'll need to know the basics of Dagster to complete this course. If you've never used Dagster before or want a refresher before getting started, check out the Dagster Essentials course.

  • Python & SQL knowledge

    While you don’t need to be a Python expert to get started, you do need some Python familiarity to complete this course and use Dagster. In Lesson 2, we’ll cover Dagster’s specific installation requirements. Here are some Pythonic skills that you’ll be using, along with resources to learn about them: Functions, Packages and Modules, Decorators, and Type Hints.

    You won’t be writing complex SQL, but you will need to understand the concept of SELECT statements, what tables are, and how to make them. If you’d like a 5-minute crash course, here’s a short article and cheatsheet on using SQL.

Course curriculum

    1. About this course & getting help

    2. What's dbt?

    3. Why use dbt and Dagster together?

    4. How do dbt models relate to Dagster assets?

    5. Knowledge check

    6. Project preview

    1. Requirements

    2. Set up the Dagster project

    3. Set up the dbt project

    4. dbt project files

    5. Verify dbt installation

    6. Knowledge check

    1. Overview

    2. Constructing the dbt project

    3. Defining the dbt project location in Dagster

    4. Creating a dbt resource in Dagster

    5. Loading dbt models into Dagster as assets

    6. Updating the Definitions object

    7. Knowledge check

    8. Viewing dbt models in the Dagster UI

    9. Knowledge check: Part 1

    10. Knowledge check: Part 2

    1. Overview

    2. Speeding up the development cycle

    3. Debugging failed runs

    4. Knowledge check

    1. Overview

    2. Connecting dbt models to Dagster assets

    3. Knowledge check

    4. Creating assets that depend on dbt models

    5. Automating dbt models in Dagster

    6. Practice: Group dbt models by layer

    1. Overview

    2. Creating a simple incremental model

    3. Creating a partitioned dbt asset

    4. Recap

Skills you'll gain in this course

  • Confidence in integrating and orchestrating your dbt projects with Dagster
  • Understanding how dbt models relate to Dagster assets
  • Ability to deploy an integrated dbt and Dagster project to production