#053: What are "intermediate" models in dbt?

I used to hear about "intermediate" dbt models, but had no idea what they were.

Many projects (and years) later, I now finally understand their value and use them regularly on implementations.

In short, the idea of intermediate models (or an intermediate layer) provide a strategy for breaking up complex queries so that your models are easier to work with & understand.

When done right, they can be extremely helpful to improve readability and maintenance long term.

But used wrong and they'll just make your project a mess that will only become more difficult to manage over time.

So in today's video I'll break down:

1. What "intermediate" models are
2. Show an example use case
3. Leave you with some tips on things to avoid

After this video, you'll be able to notice areas in your own project where you can improve through an intermediate layer. 

What will you learn? 

• What it means to have intermediate models in dbt
• How to technically add them in your project (in code)
• Tips on ways to avoid using them the wrong way

Enjoy!