Week 3: getting our hands dirty with a real dbt project
The Practice Project is now set up for Checkpoint 1.
Part of the “Mastering dbt” series. Access to the full Study Guide. Let’s connect on LinkedIn!
The third week of our journey preparing for the dbt exam saw a big milestone: the Practice Project is now live and we have outlined the tasks for Checkpoint 1.
Practicing what we are learning in the documentation is very important to cement the theory. It also exposes us to errors that we will need to debug and this is a big part of the learning curve.
Unless you are a very experienced dbt developer, I really recommend following the Practice Project checkpoints.
Table of contents:
Practice Project is now live!
Study notes added: DAG best practices
Practice Project is now live!
Our Practice Project and the tasks for the Checkpoint 1 are live now!
The internet is full of datasets to be used as practice projects. Actually, dbt’s own jaffle_shop dataset is not bad as a starter. However, in a real-life scenario, we’d rarely work with 400-row datasets.
That’s why we are going to use Leo Godin's setup:
He created a dbt project that generates fake data with new records being added every day. His tables - which are also available in a public BigQuery dataset - offer the opportunity to learn on sizeable, live datasets which emulate what we’d encounter in the real world.
I found that putting the Checkpoint 1 learnings into practice with a project really helped me visualise and make sense of some of the abstract concepts we covered. I’m excited to continue to build this Practice Project with you!
Study notes added: DAG best practices
With the Practice for Checkpoint 1 concluded, we are now entering Checkpoint 2, where we are going to deep-dive into dbt_project and source configurations, materialisations, and logging.
For now, I have added study notes for the first section where we learn how to untangle a messy DAG and make it modular and high performant:
A full list of the study notes is available in the main post.
Next week, we are going to review workflow best practices and begin to deepen our knowledge of configs for the dbt_project.yml file. I expect this to be quite a technical Checkpoint so the study notes will be very helpful to summarise it all.
Have the study notes been useful to you so far? How are you getting on with your self-paced learning journey? I would love to hear from you here or on LinkedIn!