Implementing DataOps and DevOps on Databricks
DataOps and DevOps are two methodologies that aim to improve the quality, speed, and efficiency of data and software development processes. DataOps focuses on the end-to-end orchestration of data pipelines, from data ingestion to analysis and visualization. DevOps focuses on the continuous integration and delivery of software applications, from code development to deployment and monitoring.
Databricks supports both DataOps and DevOps practices by offering various features and tools that enable users to collaborate, automate, and optimize their data and code workflows.
In the chapter, you will learn how to implement DataOps and DevOps on Databricks. We will cover the following recipes:
- Using Databricks Repos to store code in Git
- Automating tasks by using the Databricks command-line interface (CLI)
- Using the Databricks VSCode extension for local development and testing
- Using Databricks Asset Bundles (DABs)
- Leveraging...
