As the data world increasingly adopts software development concepts, the article explores the application of unit and integration testing in data contexts, highlighting tools like dbt and Great Expectations. Unit tests are designed to verify the basic functionality and handle edge cases of individual pieces of code, such as functions or classes, ensuring they behave as expected. dbt offers a straightforward framework for unit testing database tables, allowing users to specify conditions like uniqueness or non-null values with minimal configuration. Integration tests, on the other hand, ensure that different components of an application work together correctly, such as maintaining referential integrity between database tables. dbt facilitates these tests as well, enabling validation of foreign key relationships with concise YAML configurations. Great Expectations complements these capabilities by offering a Python API and an extensive library of tests, with a web UI in development, providing a robust alternative for data testing.