When working with data, you want to be sure that specific requirements and standards are satisfied by your data. When transforming and modeling the data, having a tool that automatically tests the output data could be a good solution in order to have high-quality data.

Testing is a core component when working with data, so dbt allows you to test your sources and models. You can use native dbt tests, but you can also define your own.

In this lab step, you will test your dbt sources. You will then create a custom test, and test a model both with native and custom dbt tests.

Learning Objectives

Upon completion of this lab, you will be able to:

• Understand what tests are and how to work with tests
• Create custom dbt tests

Intended Audience

• Data analysts that need to test the dbt output produced
• Developers that need to create custom dbt tests

Prerequisites

To get the most from this lab, you should have basic knowledge of dbt. To get ready, you can use the following labs:

• Create Your First dbt (Data Build Tool) Project
• Configure a dbt Profile and Define Sources
• Create and Execute Your First dbt Models
• Working With Full-Refresh dbt Models
• Working With Incremental dbt Models
• Working With Ephemeral dbt Models
• Understand and Use dbt Jinja Macros
• Understand and Work With dbt Seeds