DevOps and Development Lifecycle in Azure Databricks

Scaling data workloads requires more than just writing code; it demands robust, production-grade development processes. This text-based course guides you through establishing professional software development lifecycles directly within Azure Databricks. You will transition from writing manual notebook code to deploying fully automated, version-controlled, and tested data pipelines. What you'll learn: - Understand foundational DevOps concepts and how they apply to cloud data platforms - Configure Git integration and branching strategies within Azure Databricks Repos - Implement testing patterns for notebooks and libraries using Python testing frameworks - Manage environment configurations and secrets securely - Deploy infrastructure and workflows programmatically using Databricks Asset Bundles and the Databricks CLI - Design basic CI/CD pipeline workflows for continuous integration and delivery The course begins with core lifecycle concepts and Git integration basics before moving into testing strategies, environment configuration, and automated deployments. You will learn through clear, written explanations, configuration examples, and step-by-step implementation scenarios. This course is designed for beginner data engineers, analysts, and cloud practitioners looking to adopt professional software engineering practices in Databricks. No advanced DevOps experience is required. Start building reliable, automated data pipelines in Azure Databricks today.