Demos

Import the following notebooks in the Databricks workspace to try DQX out:

Use as Library

• DQX Quick Start Demo Notebook (library) - quickstart on how to use DQX as a library.
• DQX Demo Notebook (library) - demonstrates how to use DQX as a library.
• DQX Lakeflow Pipelines Demo Notebook - demonstrates how to use DQX with Lakeflow Pipelines (formerly Delta Live Tables (DLT)).
• DQX Asset Bundles Demo - demonstrates how to use DQX as a library with Databricks Asset Bundles.
• DQX Demo with dbt - demonstrates how to use DQX as a library with dbt projects.

Deploy as Workspace Tool

• DQX Demo Notebook (tool) - demonstrates how to use DQX as a tool when installed in the workspace.

Use Cases

• DQX for PII Detection Notebook - demonstrates how to use DQX to check data for Personally Identifiable Information (PII).
• DQX for Manufacturing Notebook - demonstrates how to use DQX to check data quality for Manufacturing Industry datasets.

Execution Environment

You don't have to run DQX from a Notebook. DQX can be run from any Python script as long as it runs on Databricks. For example, you can run it from a Databricks job by adding DQX as a dependent library. When DQX is installed in the workspace as a tool, it provides a suite of command-line tools for executing DQX jobs (see the User Guide).