1. Introducing the dbt case study
Welcome to the dbt case study course! My name is Susan. Come on in and let's get started.
2. Why dbt?
As a data scientist with more than 15 years of experience, I've worked with everything from small three-man start-ups to large tech giants like Google and international entities like the United Nations.
One thing all these organizations share in common, is a strong data architecture to leverage data for better decision-making, scalability, and compliance.
This is also why I've used dbt across so many sectors. dbt has become increasingly popular in all fields, from e-commerce to renewable energy, because of its ability to streamline the data transformation process and to integrate smoothly with the modern analytics stack.
3. A preview of what we are building
In this course, we will be learning and building as analytical engineers at an e-commerce company.
Using six non-trivial data files as a starting point, we will build for our internal stakeholders: the data and product teams. We will create a complex and rich dbt data pipeline like the one shown here, so that our stakeholders can focus on using clean data to answer critical business questions about our customers and our products.
4. A preview of what we are building
So how do we get started?
Step by step, we will incrementally build out a dbt project using our IDE exercises. Toward the end of this course, our finished code repository will look something like this.
In the following exercises, we will first check our dbt installation and initialize our dbt environment.
Here's a recap of the dbt commands we will need.
5. Let's practice!
Ready to build? Let's go!