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.