Course
Case Study: Building E-Commerce Data Models with dbt
AdvancedSkill Level
Updated 01/2026dbtData Engineering4 hr7 videos31 Exercises2,750 XP2,789Statement of Accomplishment
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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
Data Manipulation in SQLIntermediate dbt1
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.
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
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FAQs
Do I need prior experience with dbt before taking this case study?
Yes, this course is designed for early-stage dbt users. You should complete Introduction to dbt and Intermediate dbt first, along with several SQL prerequisites.
What e-commerce scenarios does this case study cover?
You build a full ELT pipeline for an e-commerce dataset, including staging models, data mart models for business needs, data quality tests, and Jinja-enhanced transformations.
How is the course structured across the three chapters?
Chapter 1 covers project setup and staging models. Chapter 2 focuses on building the data pipeline from staging to data mart models. Chapter 3 introduces Jinja for streamlining your dbt code.
Will I learn how to write data quality tests in dbt?
Yes, Chapter 2 teaches you to create data tests that guard against data quality drift as you build your pipeline from staging to final mart models.
What role does Jinja play in this course?
In Chapter 3, you learn to use Jinja variables, loops, and macros to reduce redundancy and improve the maintainability of your dbt transformation workflows.
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