Creating a Data Model w/ dbt: Dimensions (Part 1/3)

A big challenge for data teams continues to be successfully creating a clear data model.

While tools like dbt make it easier than ever to actually write the code...

The design component still requires your own strategic thinking to get it done.

However, when you're able to combine a great tooling option like dbt with a simple but clear modeling strategy...

It can be a recipe for great long-term success on the data modeling front.

With that in mind, starting today and over the next few videos, I'll be sharing a few lessons from a prerecorded training on the topic data modeling.

In it, I walk through the steps to create your own, what I call "Warehouse Layer" in your project with dbt.

In this first video, we're going to start with creating Dimension tables.

Then, over the next two weeks we'll move to creating a Fact table and finally implementing some baseline Tests.

Each each, you'll see how to:

• Leverage configurations of dbt
• Align with the strategy of star schema dimensional modeling
• Structure model queries themselves

For now, let's get started with Part 1: Dimensions.

Enjoy.