Build your ultimate AI agent
Course Description
Transform raw data into clean, reliable models using dbt (Data Build Tool) - a modern, SQL-based transformation framework used by data teams around the world. This hands-on case study course is designed for early-stage learners who want to build real-world skills through guided, practical exercises. You'll set up your own dbt environment, model data at scale, and write reusable code using dbt's built-in features.
Set Up Your Project and Explore the Data
Get started by setting up a dbt project and working with a real E-Commerce dataset. You'll structure raw data, configure profiles, and debug syntax issues while gaining insight into the business context behind each transformation step.Build and Validate Models
Learn to create scalable staging models and apply data quality checks to ensure your datasets are accurate and analysis-ready. You'll build a solid foundation for answering key business questions.Automate with Jinja
Finish the course by learning how to use Jinja to write reusable, maintainable code. You'll use variables, control flow, and loops to follow the DRY (Don't Repeat Yourself) principle to streamline your dbt workflow.Prerequisites
Curriculum
Course outline
1
Setting up dbt
Get practice building a dbt project from the ground up. Apply your skills at loading different types of data into the dbt project and setting up a variety of staging dbt models. This chapter focuses on the E and L parts of the ELT process.
- Introducing the dbt case study50 XP
- Check dbt installation100 XP
- Initialize the dbt project100 XP
- Setting up the dbt project and loading data50 XP
- Load distribution center as a dbt seed file100 XP
- Create distribution center staging model100 XP
- Load and create user model via dbt source100 XP
- More practice with dbt source and staging models100 XP
- Debug common errors100 XP
2
Building dbt models
Dive deep into the weeds of dbt data modeling. Build the data pipeline from preliminary staging models to the final data mart models for answering critical business needs. Along the way, get experience creating data tests to guardrail against data quality drift.
3
Improving dbt with Jinja
Learn to enhance your dbt projects with Jinja by streamlining code, reducing redundancy, and improving maintainability. You'll practice using variables, loops, and macros to build more efficient transformation workflows.
Case Study: Building E-Commerce Data Models with dbt
Course
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