What is the primary function of singular tests in dbt?

The primary function of singular tests in dbt is to write SQL that returns failing records. Singular tests are designed to validate a specific condition or set of conditions in your data. When a singular test is executed, it runs the SQL logic you’ve defined, and if that logic identifies any records that do not meet the specified criteria, those records are returned as the failing cases.

This type of testing allows you to enforce quality checks on your data. For example, you can use singular tests to ensure that certain fields are not null, or that the values in a column fall within a specified range. The key aspect is that the SQL you write must clearly reflect the conditions you want to validate, and failing records will be those that do not conform to those conditions.

In contrast, the other options refer to different functionalities within dbt's testing framework. Assessing the freshness of sources relates to ensuring that data inputs are up to date. Defining accepted values pertains to constraints or enumerations that limit what can be entered into a field. Validating data types across models typically involves checks on the structure and type consistency of data, which is not the primary role of singular tests. Therefore, the focus of singular tests specifically on querying for failing records sets it apart