Case Study: Building E-Commerce Data Models with dbt

Overview

Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.

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.

Syllabus

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.

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.

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.