Week 5: 3 thoughts from by talk at dbt Labs + Materialisations
I got to chat with other dbt nerds at the HQ in Dublin and had some insights. Plus, we covered 3 basic materialisation types.
Part of the “Mastering dbt” series. Access to the full Study Guide. Let’s connect on LinkedIn!
Last week, I had a major deadline from a client and had a lot of moving around to do (#digitalnomadproblems). This meant I did not get a lot done in terms of study notes, but it was still a big week: I got to speak at the dbt Labs officei in Dublin!
Study notes added:
We started going through the 3 basic materialisation types in the post below. We will cover Incremental and Materialised Views in the next Checkpoints, but I decided to stick to the basics for now.
A full list of the study notes is available in the main post.
This week, we are going deep-dive into two resources: models and sources. Then, we will go through node selectors and errors & debugs.
3 thoughts from my talk at dbt Labs Dublin
Last Thursday, I had the pleasure of introducing this very Study Guide to aspiring and current developers at the dbt Labs office in Dublin. I came out feeling inspired by the conversations I had and decided to share 3 main insights here.
This project is more than just an exam prep:
From my conversations with dbt beginners, I realised that this Study Guide is not only for people who want to become certified, but for anyone who wants to learn dbt on their own. This has given me ideas for the future of this project.
We forget how powerful in-person conversations are
It was so enlightening to talk about dbt and this project to other people in person. When you create things on your own, you can’t truly gauge how people perceive your project. It was great to hear their enthusiasm and questions about the project.
Why are so many analysts tired of their jobs?
I know we were a small sample, but I met so many analysts who resonated with my experience of feeling stagnated at my data job and looking to upskill. It made me think that maybe companies need to dedicate more energy to the career progression of their data teams.
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!