Unit Testing DLT for Production-Grade Pipelines

Production-grade pipelines require unit tests to guarantee their robustness. DLT lets you track your pipeline data quality with expectation in your table.

These expectations can also be leveraged to write integration tests, making robust pipelines.

In this demo, we’ll show you how to test your DLT pipeline and make it composable, easily switching input data with your test data.

 

To install the demo, get a free Databricks workspace and execute the following two commands in a Python notebook

Dbdemos is a Python library that installs complete Databricks demos in your workspaces. Dbdemos will load and start notebooks, DLT pipelines, clusters, Databricks SQL dashboards, warehouse models … See how to use dbdemos

 

Dbdemos is distributed as a GitHub project.

For more details, please view the GitHub README.md file and follow the documentation.
Dbdemos is provided as is. See the License and Notice for more information.
Databricks does not offer official support for dbdemos and the associated assets.
For any issue, please open a ticket and the demo team will have a look on a best-effort basis.

 

Note - at Data + AI Summit in June 2025, Databricks released Lakeflow. Lakeflow unifies Data Engineering with Lakeflow Connect, Lakeflow Declarative Pipelines (previously known as DLT), and Lakeflow Jobs (previously known as Workflows).