Master dbt Workflows
Take your dbt skills to the next level and learn how to implement robust, scalable data transformation workflows in a production environment. This course is designed for data engineers, analysts, and analytics engineers who want to move beyond the basics and gain hands-on experience with advanced dbt functionality.
Ensure Data Quality with Advanced Testing
Building reliable data pipelines starts with validation. You'll explore advanced testing techniques to catch data inconsistencies, create custom reusable tests to standardize validation across models, and apply tests to sources and seeds for better governance and data lineage tracking.
Leverage dbt Sources, Seeds, and Snapshots
Discover how dbt sources can improve documentation and lineage while ensuring traceability of raw data. Learn to use dbt seeds for managing small, static datasets efficiently. Then, master slowly changing dimensions (SCD2) with dbt snapshots, allowing you to track historical changes in your data warehouse with minimal effort.
Automate and Optimize with dbt Build
Efficiency is key in production environments. You’ll learn how to streamline workflows with dbt build, automating model execution, tests, and snapshots to ensure reliable transformations. By optimizing your pipeline, you'll enhance performance, maintainability, and scalability of your dbt projects.
Apply Your Skills in Real-World Scenarios
Through interactive exercises and hands-on practice, you’ll reinforce your knowledge and gain the confidence to apply dbt in real-world settings. By the end of the course, you'll be equipped to design, test, and automate production-ready dbt workflows, ensuring high-quality and well-documented transformations at scale.
