What is a Databricks notebook?

A Databricks notebook serves as an interactive web-based interface where users can write code, visualize data, and document their workflow. This environment supports multiple programming languages like Python, SQL, Scala, and R, allowing data scientists and engineers to combine code execution, results, and narrative text in one cohesive platform.

The design of notebooks encourages collaboration, enabling different team members to share insights and findings efficiently. Users can embed visualizations directly alongside code, making it easier to interpret results within the context of their analysis. This synergy promotes an interactive approach to data exploration and helps streamline the data science workflow.

While the other choices mention relevant tools and platforms within the broader data ecosystem, they do not encapsulate the core functionalities of a Databricks notebook. A desktop application for data visualization would not provide the coding and documentation features integral to a notebook. A command-line tool for managing libraries focuses on library administration, which is separate from the analysis tasks typically performed within a notebook. Lastly, a cloud storage platform for big data does not reflect the interactive capabilities of notebooks, which include coding, execution, and immediate feedback through visualization.