Running tests with dbt test

Introduction

Running tests with dbt test helps you check your data for mistakes or problems automatically. It makes sure your data is clean and reliable.

After adding new data models to check if the data meets your rules.

Before sharing reports to ensure data quality.

When fixing data issues to confirm the problem is solved.

Regularly in your data pipeline to catch errors early.

Syntax

dbt

dbt test [--select <models>] [--exclude <models>] [--store-failures] [--data] [--schema]

dbt test runs tests defined in your project on your data models.

You can select specific models to test or exclude some using flags.

Examples

Runs all tests defined in your dbt project.

dbt

dbt test

Runs tests only on the customers model.

dbt

dbt test --select customers

Runs tests on all models except orders.

dbt

dbt test --exclude orders

Runs tests and saves any failing rows to a table for review.

dbt

dbt test --store-failures

Sample Program

This example shows how to define simple tests to check that the email column in the customers model is never empty and has unique values. Then, running dbt test --select customers checks these rules.

dbt

1. Define a test in your model's schema.yml file:

version: 2
models:
  - name: customers
    columns:
      - name: email
        tests:
          - not_null
          - unique

2. Run the test in terminal:

$ dbt test --select customers

Important Notes

Tests can be schema tests (check structure like uniqueness) or data tests (custom SQL queries).

Use --store-failures to save failing rows for easier debugging.

Running tests regularly helps keep your data trustworthy.

Summary

dbt test runs checks on your data models to find errors.

You can run tests on all or specific models using flags.

Defining tests in schema.yml files helps automate data quality checks.