Bringing Structured Testing to Databricks Projects
Databricks offers a powerful and flexible environment for building data pipelines, but unlike some tools, it doesn’t provide a built-in framework for testing. This can leave data engineers wondering how to effectively validate their work.
In this session, Ioseb Laghidze will guide you through practical approaches to integrate structured testing into your Databricks projects. We’ll draw inspiration from established software engineering techniques to address common testing challenges. You’ll learn how to:
Modularize PySpark transformations for efficient unit testing.
Set up containerized environments with PySpark, Delta, and Kafka for seamless local development.
Implement integration tests that accurately simulate real-world data flows.
We’ll also explore how these testing practices can be seamlessly incorporated into your CI/CD workflow, ultimately building greater confidence in your production data pipelines.
