What is the primary use of a Databricks notebook?

The primary use of a Databricks notebook centers around visualizing outputs and sharing insights. Databricks notebooks provide an interactive environment where data scientists and engineers can write code, run data processing tasks, and visualize data directly in the notebook interface. This interactivity allows for real-time feedback, making it easy to iterate on analyses and quickly adjust visualizations based on the results.

Within the Databricks platform, notebooks are also designed to facilitate collaboration. Team members can comment on specific sections of the code, share findings, and embed visualizations to communicate their insights effectively. This aspect of sharing and visualizing results is crucial in data-driven environments, as it allows stakeholders to understand and act upon the data more readily.

While data storage and management, code execution across platforms, and data integration with external sources are significant capabilities within the Databricks ecosystem, they are secondary functions in relation to the primary purpose of the notebook. The notebook serves as an interface for executing code and demonstrating data insights rather than focusing solely on data management or integration tasks.