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Vibe Harboe Christensen has completed

Intermediate dbt

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2 hr
2,150 XP
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Course Description

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.

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  1. 1

    Testing & Documentation

    Free

    Learn how to ensure data quality with advanced testing techniques in dbt. Explore built-in, singular, and reusable tests to validate models, sources, and seeds. Understand how to define custom tests using Jinja, troubleshoot failures, and optimize your validation workflow to catch inconsistencies before they impact downstream analysis.

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    Introduction to testing in dbt
    50 xp
    Built-in tests
    100 xp
    Defining tests on a model
    100 xp
    Finding bad data
    100 xp
    Creating singular tests
    50 xp
    Steps to develop a singular test
    100 xp
    Verifying trip duration
    100 xp
    Verifying test queries
    100 xp
    Creating custom reusable tests
    50 xp
    Testing, testing, testing
    100 xp
    Implementing a reusable test
    100 xp
    Updating from singular to reusable test
    100 xp
  2. 2

    Implementing dbt in production

    Take your dbt skills to the next level by implementing scalable, production-ready workflows. Learn how to use dbt sources and seeds to improve data lineage, implement snapshots for tracking historical changes, and automate your transformations with dbt build. By the end, you’ll be equipped to manage large-scale data pipelines with confidence.

    Play Chapter Now
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

collaborators

Collaborator's avatar
George Boorman
Collaborator's avatar
Arne Warnke

prerequisites

Introduction to dbt
Mike Metzger HeadshotMike Metzger

Data Engineer Consultant @ Flexible Creations

Mike is a consultant focusing on data engineering and analysis using SQL, Python, and Apache Spark among other technologies. He has a 20+ year history of working with various technologies in the data, networking, and security space.
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