Introduction to dbt: Learn and Test Your Data Modeling Skills

Modern data teams rely on clean, reliable, and well-documented data pipelines. If you want to transform raw data in your warehouse using software engineering best practices, learning dbt (data build tool) is the essential first step. This text-based course guides you through the foundational concepts of dbt, helping you transition from writing messy SQL scripts to building structured, version-controlled data models. You will read clear explanations, analyze modular code patterns, and reinforce your learning with written conceptual quizzes at every step. What you will learn: 1. Understand core analytics engineering principles and how dbt fits into the modern data stack. 2. Configure dbt projects, models, and sources using modular SQL and YAML files. 3. Apply data testing and documentation practices to ensure high-quality data pipeline outputs. 4. Learn modern deployment strategies, including version control integration and dbt Cloud basics. 5. Practice your knowledge with built-in written quizzes and self-assessment scenarios designed for self-study. The course begins with key terminology and foundational data warehousing concepts before moving into model creation, testing frameworks, and documentation standards. You will progress from basic SELECT statements to deploying structured data transformations. This course is designed for beginner data analysts, aspiring analytics engineers, and database administrators with no prior dbt experience. A basic understanding of SQL is recommended. Start reading today to build a solid foundation in modern data transformation.