Test severity levels in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What are the common test severity levels in dbt?

The common test severity levels in dbt are error and warn. <br> - error: Fails the run if the test fails. <br> - warn: Logs a warning but does not fail the run.

beginner

How does setting a test severity to 'warn' affect a dbt run?

Setting a test severity to 'warn' means that if the test fails, dbt will log a warning message but will not stop or fail the entire run. This allows the pipeline to continue while highlighting potential issues.

beginner

What happens when a dbt test with severity 'error' fails?

When a dbt test with severity 'error' fails, the entire dbt run stops and fails. This is used for critical tests where failure means the data or model is not reliable.

intermediate

How do you specify test severity in a dbt schema.yml file?

In the schema.yml file, you specify severity inside the test configuration like this:<br>

tests:<br>  - unique:<br>      severity: warn

<br>This sets the test severity to 'warn' for that test.

intermediate

Why is it useful to have different test severity levels in dbt?

Different severity levels let you control how strict your data quality checks are.<br> - Use 'error' for critical checks that must pass.<br> - Use 'warn' for less critical checks to monitor issues without stopping the pipeline.<br>This helps balance reliability and workflow continuity.

What does a test severity of 'warn' do in dbt?

A Automatically fixes the data issue

B Fails the run if the test fails

C Ignores the test completely

D Logs a warning but continues the run

A 'warn' severity logs a warning when the test fails but does not stop the dbt run.

Which severity level causes dbt to stop the run on test failure?

A warn

B error

C info

D debug

The 'error' severity causes dbt to fail and stop the run if the test fails.

Where do you set the severity level for a dbt test?

A In the schema.yml file under the test configuration

B In the dbt run command

C In the model SQL file

D In the dbt_project.yml file

Severity is set in the schema.yml file inside the test configuration.

Why might you use 'warn' instead of 'error' for some tests?

A To allow the pipeline to continue while monitoring issues

B To speed up the dbt run

C To ignore the test results

D To automatically fix data errors

'warn' allows the pipeline to continue but still alerts you to potential data issues.

What is the default severity level if none is specified in dbt tests?

A info

B warn

C error

D debug

By default, dbt treats tests as 'error' severity if not specified.

Explain the difference between 'warn' and 'error' severity levels in dbt tests.

Think about how each severity affects the dbt run behavior.

Describe how to set a test severity level in a dbt schema.yml file with an example.

Look at the test configuration block in schema.yml.