Learn DBT from Scratch

What you'll learn

Welcome to this course, Learn DBT from Scratch. DBT lets you build a system of transformations on your data, with tests, scheduled runs, multiple environments, flexibility, and more all without needing a team of engineers to set up and manage your workflow. By the end of this course, you will have:

• set up DBT locally and on the cloud

• connected DBT to Snowflake (or a data warehouse of your choice)

• create your own SQL transformations on data

• test your transformations

• snapshot your data to keep track of how your data changes over time

• learn DBT best practices

In this course, you'll be presented with the summarized information you need so that you can quickly get DBT implemented in your data pipeline (or in a brand new, data warehouse).

Why you should learn DBT

DBT is not one of the first technical skills most Data Scientists or Analysts think to learn. It’s not as exciting as machine learning algorithms, and it’s not as easy to show off as a fancy data visualization.

But DBT is an absolutely fundamental skill for any Data Scientist or Analyst due to all of its capabilities. Because DBT is so flexible, there are almost an endless amount of ways you can integrate DBT into your data architecture. Some features that DBT provides you that all Data Scientists and Analysts should be using in their work include:

1. Creating consistent aggregations for your analysis in a single location

2. Consistently testing your transformations and underlying data

3. Running your data transformations on a schedule

4. Test your code in a DEV environment

About DBT

DBT is pioneering modern analytics engineering. DBT applies the principles of software engineering to analytics code, an approach that dramatically increases your leverage as a data analyst. They believe that data analysts are the most valuable employees of modern, data-driven businesses and they build tools that empower analysts to own the entire analytics engineering workflow.