Getting started with dbt™
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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™
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.
📌 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.