Advanced dbt-GA4 (On-Demand)

Go beyond the basics of the dbt-GA4 package. Build the data engineering foundation you need to deliver high-value insights and advance your career.

Moving from Beginner to Advanced dbt via dbt-GA4

You’re an analyst. You know your way around GA4. And you know its limitations so you’ve started diving in to BigQuery.

You followed the instructions in the dbt-GA4 Setup course and have the package installed and running.

But now you’re getting questions about how to use this data:

• Can you set up a funnel report for me?
• Can you customize the channel groupings?
• Why do my reports take forever to load?
• Can you do this now with Google and Facebook Ads data?

If this sounds familiar, you’re ready for the next step.

This course is the bridge from using your dbt, Git, and BigQuery data engineering stack to mastering it. You will learn to architect solutions in a real-world GA4 environment solving problems and extracting value from your warehouse.

Who Is This Course For?

This course is designed for the Google Analytics specialist who is getting into BigQuery to do more with their GA4 data. This is for you if want to:

• Break free from the limitations of the basic GA4 interface.
• Solve business problems beyond the reach of the GA4 interface.
• Build the foundation of a data engineer—equipping yourself with the core skills to tackle technical challenges independently.

While valuable for other data roles, this course is written for Google Analytics professionals.

Before You Enroll: Technical Requirements

This is an advanced, hands-on course, which means we have a few non-negotiable requirements.

Please make sure you have the following before you join:

1. A BigQuery Project with a Billing Account: You must have a Google Cloud project with an active billing account. The free BigQuery sandbox will not work because it disables specific permission that dbt needs to work.
2. A Live GA4 Data Stream: You must have a real GA4 property actively exporting data to your BigQuery project. It doesn’t have to be a high-traffic site, but it must be live.

Why can’t I use the public dataset? The public ga4_obfuscated_sample_ecommerce dataset will not work for this course. The dbt-GA4 package uses a date lookback (e.g., “last x days”) to process data. Because the public data is static and several years old, the models will fail to find new records to process.

What about the setup? We do a light review of the basic setup covered in the dbt-GA4 Setup course.

• If you took the Setup course: You can continue using that same project—just skip the tasks you’ve already completed.
• If you are an experienced dbt user: You might be able to skip the Setup course, provided you are using the native GA4 BigQuery integration (configured directly in the GA4 interface). Third-party API exports offer pre-aggregated stats; we need the raw, event-level granularity of the native export so we can model logic that doesn’t exist in the standard API.

This Course is Different

This isn’t a “hello world” tutorial—it is an advanced course designed to teach you how to think, build, and scale like an analytics engineer.

Instead of multiple-choice quizzes and copy-paste code, you will learn by doing. You will work on a real-world project (your own data), using a structure designed to build deep, lasting knowledge.

By the end of this course, you will be able to:

• Configure the dbt-GA4 package internals to fully optimize performance and cost.
• Construct efficient reporting models that answer your business’s unique questions.
• Architect solutions that build on the package’s foundation.
• Lead the implementation lifecycle, from gathering requirements to facilitating IT kickoff calls.
• Translate abstract business requirements into concrete data models using a “plan-first” approach.
• Develop the core analytics engineering skills needed to confidently tackle any new data challenge.

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What’s Inside the Course?

We’ve structured the curriculum to take you step-by-step from a basic setup to a fully-custom, production-grade dbt project.

Each chapter provides one practical goal that you will work towards. While doing so, you will review previous lessons, learn important new concepts, and then practice and apply them.