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Intermediate dbt
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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.
Prerequisites
Introduction to dbtTesting & Documentation
Implementing dbt in production
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FAQs
What dbt skills should I have before taking this intermediate course?
You should have completed Introduction to dbt along with intermediate SQL and shell basics. Familiarity with dbt models, materializations, and the dbt CLI is expected.
What testing strategies does this course cover beyond built-in tests?
You will learn singular tests for one-off validations, reusable custom tests written in Jinja, and techniques for troubleshooting failures and optimizing your testing workflow.
Does the course explain dbt snapshots for tracking data history?
Yes. You will implement snapshots to track historical data changes over time, which is essential for slowly changing dimensions and auditing data in production pipelines.
What production workflow topics are included?
You will learn to use dbt sources and seeds to improve data lineage, automate transformations with dbt build, and manage large-scale data pipelines with confidence.
Who is this course designed for?
Data engineers and analytics professionals who already use dbt for basic transformations and want to add advanced testing, documentation, and production deployment skills.
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