Introduction to dbt

Overview

This course introduces dbt for data modeling, transformations, testing, and building documentation.

This course introduces you to dbt (data build tool), a popular tool that has given rise to analytics engineering for the creation and maintenance of extract, transform, and load (ELT) pipelines. You'll learn to build data warehouses, perform data modeling and transformations, and design tests to perform data validation. You'll use SQL and shell commands to perform a variety of tasks with dbt, along with discovering how to generate documentation for your warehouse users!

Syllabus

Welcome to dbt

Learn about the reasons behind dbt's existence and how it's used to create data transformation projects.

dbt models

Get into the true substance of dbt by working with data models and creating SQL based models within dbt. Learn about basic SQL models, define dependencies, update, and troubleshoot various model issues.

Testing & Documentation

Learn to take advantage of data validation in dbt using tests. Apply default tests to various models and properties, then create custom tests to handle specialized logic validation. Learn to document various details of dbt models and generate lineage information automatically.

Implementing dbt in production

Utilize what you've learned about dbt with some added details to implement dbt in a production environment. We'll cover dbt seeds and snapshots, along with how to automate builds. Finally review what you've learned throughout the course and implement a dbt pipeline.