What is the purpose of Databricks Workflows?

The purpose of Databricks Workflows is to automate and schedule tasks such as running notebooks and jobs. Workflows enable users to orchestrate complex data pipelines and automate repetitive tasks, enhancing efficiency in data engineering, machine learning, and data science tasks. With Workflows, users can define a series of steps that can run at specified times or trigger based on certain events, making it easier to manage data processing and analysis tasks within Databricks.

While generating automated reports, visualizing data trends, and managing user permissions may be relevant activities in a data environment, they do not represent the primary function of Databricks Workflows. Workflows are specifically designed to handle task automation and scheduling, which is crucial for maintaining streamlined operations and ensuring timely data processing.