Getting started with dbt™

An introduction to dbt™ for beginners, covering core concepts, project structure, models, sources, and testing to help you build reliable data transformations.

Getting Started with dbt™

dbt™ (Data Build Tool) is a transformation framework that enables data teams to apply software engineering best practices to analytics workflows. This section provides a high-level introduction to dbt™, how it fits into the modern data stack, and how to structure your dbt™ projects effectively.

If you're new to dbt™, this guide will walk you through the key concepts of dbt™

Explore the Basics of dbt™

📌 1. Introduction

Understand how dbt™ improves data transformations, version control, and testing in the modern data stack.

📁 2. Project Structure

Learn how dbt™ projects are structured, including key files like dbt_project.yml, models, sources, and dependencies.

🔗 4. Working with Sources

Define and manage raw data sources using sources.yml, ensuring consistency, documentation, and data freshness.

📊 3. Models and Transformations

Discover how dbt™ models work, including ref(), materializations, and Jinja for dynamic transformations.

🛠️ 5. Testing Data Quality

Explore dbt™ testing, including built-in and custom tests to validate data integrity and enforce business rules.

Prefer hands-on learning? Check out our Paradime 101 Guide for a step-by-step, interactive way to learn dbt™ and analytics engineering best practices—all for free.