Creating a Workspace
Last updated
Last updated
In this guide, you'll learn all the essential steps to create a Paradime workspace, the foundation for your dbt™ development journey. A well-configured workspace is crucial for efficient collaboration and streamlined analytics engineering processes.
Estimated completion time: 10 minutes
An admin role In Paradime to create workspaces
Repository admin access to add a deploy key for your Git repository
Access credentials for your data warehouse
In this guide, you'll learn how to:
The following video provides step-by-step instructions for creating a workspace, connecting a Git repository, and setting up a data warehouse connection:
To create a workspace in Paradime:
Navigate to your Platform settings.
Click the New Workspace
button to begin setting up your workspace.
Provide a name for your workspace.
Choose whether you want other people in your organization to access it without an invite (with a business user role). This option makes the workspace visible in the workspaces list to users, even if they're not yet part of it.
Next, connect a Git repository to Paradime:
This can be an empty repository or an existing dbt™ project.
Upon adding a repository SSH URI, Paradime will generate a deploy key.
Use this deploy key to grant Paradime write access to the repo, allowing users to create commits and push branches from the Paradime IDE.
Note: You must be a repository admin to add a deploy key. Paradime supports GitHub, GitLab, Azure Repos, and Bitbucket.
Finally, add a data warehouse connection during the workspace onboarding:
This enables developing and running dbt models via the Paradime IDE.
Paradime supports many warehouse providers, including:
Multiple authentication methods are available based on your needs.
You've successfully created your Paradime workspace, which serves as the foundation for your dbt™ development. Here's what you've accomplished:
Created a new workspace in Paradime
Connected a Git repository to your workspace
Set up an initial data warehouse connection
In the next guide, we'll explore how to configure additional data warehouse connections for development, testing, and production environments.