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
Stefano studies Computer Science and is passionate about technology. He loves working with Cloud services and learning all the best practices for them. Google Cloud Platform and Amazon Web Services are the cloud providers he prefers. He is a Google Cloud Certified Associate Cloud Engineer. Node.js is the programming language he always uses to code. When he's not involved in studying or working, Stefano loves riding his motorbike and exploring new places.