What is a primary characteristic of a Databricks notebook?

A primary characteristic of a Databricks notebook is its support for multiple programming languages. This flexibility allows users to work with different languages such as Python, Scala, R, and SQL within the same notebook. This versatility is particularly advantageous in a data engineering and data science context, where different tasks may require different languages for optimal performance and ease of use.

For instance, a user can read data with Python, perform transformations with Scala, and then utilize SQL for querying—all within a single notebook. This capability encourages collaboration among team members with different expertise and allows data scientists and engineers to choose the best language suited for their analytical tasks.

In contrast, the other options do not accurately reflect the capabilities of Databricks notebooks. The first option suggests exclusivity to Python, which is not the case, while the third option misrepresents the notebook's function by categorizing it primarily as a data visualization tool, ignoring its broader use for code execution and data manipulation. The fourth option incorrectly implies that using Databricks notebooks comes with specific software installation requirements, while in reality, Databricks provides a cloud-based environment that eliminates the need for such installations.