# Setting Up CI/CD and Unit Testing in Databricks for Reliable Data Pipelines

> In this video, Zach walks through the process of setting up Continuous Integration/Continuous Deployment (CI/CD) and unit testing in Databricks, with a particular emphasis on enhancing the reliability of data pipelines. He begins by creating a Git folder for an Airflow DBT project and explore the Y…

- Web page: https://www.dataexpert.io/lesson/setting-up-ci-cd-and-unit-testing-in-databricks-for-reliable-data-pipelines-may2025-p736-l1195
- Program: [DataExpert](https://www.dataexpert.io/program/data-expert)
- Module: Week 2: Databricks & Advanced Spark
- Access: Requires enrollment in DataExpert
- Length: 46 min video
- Skills: Python, MLOps, ETL/ELT, Airflow, dbt, Git, Databricks, CI/CD
- Academy: DataExpert.io Academy

## About this lesson

In this video, Zach walks through the process of setting up Continuous Integration/Continuous Deployment (CI/CD) and unit testing in Databricks, with a particular emphasis on enhancing the reliability of data pipelines. He begins by creating a Git folder for an Airflow DBT project and explore the YAML configuration for GitHub Actions, which will trigger tests upon pull requests. The demonstration includes running unit tests and addressing bad data scenarios, highlighting the critical importance of ensuring accurate data transformations.

## Navigation

- Previous lesson: [Apache Spark Unit Testing Day 3 Lab](https://www.dataexpert.io/lesson/apache-spark-unit-testing-day-3-lab-may2025-p736-l1148.md)
- Next lesson: [Databricks and Advanced Spark Day1 Lecture](https://www.dataexpert.io/lesson/databricksandadvancedsparkday1lecture-feb26-p736-l2025.md)