Data Science & Engineering workspace
An Azure Databricks workspace is an environment for accessing all of your Azure Databricks assets. The workspace organizes objects (notebooks, libraries, and experiments) into folders, and provides access to data and computational resources such as clusters and jobs.
You can manage the workspace using the workspace UI, the Databricks CLI, and the Databricks REST API reference. Most of the articles in the Azure Databricks documentation focus on performing tasks using the workspace UI.
Use the sidebar
You can access all of your Azure Databricks assets using the sidebar. The sidebar’s contents depend on the selected persona: Data Science & Engineering, Machine Learning, or SQL.
By default, the sidebar appears in a collapsed state and only the icons are visible. Move your cursor over the sidebar to expand to the full view.
To change the persona, click the icon below the Databricks logo , and select a persona.
To pin a persona so that it appears the next time you log in, click next to the persona. Click it again to remove the pin.
Use Menu options at the bottom of the sidebar to set the sidebar mode to Auto (default behavior), Expand, or Collapse.
When you open a machine learning-related page, the persona automatically switches to Machine Learning.
Switch to a different workspace
If you have access to more than one workspace in the same account, you can quickly switch among them.
- Click in the lower left corner of your Azure Databricks workspace.
- Under Workspaces, select a workspace to switch to it.
To get help:
Click the Help in the lower left corner:
Select one of the following options:
- Help Center: Submit a help ticket or search across Azure Databricks documentation, Azure Databricks Knowledge Base articles, Apache Spark documentation, and Databricks forums.
- Release Notes: View Azure Databricks Release notes.
- Documentation: View Azure Databricks Documentation.
- Knowledge Base: View Azure Databricks Knowledge Base.
- Databricks Status: View Azure Databricks status by region.
- Feedback: Provide Azure Databricks product feedback.
The following articles give an overview of workspace assets, how to work with workspace folders and other objects, and how to find IDs for your workspace and assets: