Creating an analytics project (Watson Studio and Watson Knowledge Catalog)

You create an analytics project to work with data and other assets to achieve a particular goal, such as building a model or integrating data. You can create an empty project, start from a sample project that provides sample data and other assets, or import a previously exported project.

Required permissions
You must have one of these user permissions to create a project:

Your project resources can include data, collaborators, tools, and operational assets that run code, like notebooks and models.

To create a project:

  1. Choose Projects > All projects from the menu and then click New project on the Projects page.
  2. Select Analytics project and click Next.
  3. Choose whether to create an empty analytics project, a project from file, or a project integrated with a Git repository.

  4. If you create an empty analytics project, you have these project configuration options:

    • Mark the project as sensitive. The project has a sensitive tag and project collaborators can't move data assets out of the project. You can enable or disable this option at any time on the project Settings page.
    • Log project activity. Detailed project activity is tracked in a full activities log that you can download. You can enable or disable this option at any time on the project Settings page.

  5. If you create a project from file, select the project ZIP file on your local system to upload. You can import a project from a file on your local system only if the ZIP file that you select was exported from an IBM Cloud Pak for Data project as a compressed file. The project ZIP file that you import must be from the same Cloud Pak for Data version you are currently using or from earlier versions. You cannot select a compressed file that was exported from a project in Cloud Pak for Data as a Service.

    If the exported file that you select to import was encrypted, you must enter the password that was used for encryption to enable decrypting sensitive connection properties. If you enter an incorrect password, the project file imports successfully, but sensitive connection properties are falsely decrypted.

    Note that if the ZIP file contains notebooks, you can only work with those notebooks in the notebook editor, even if the notebooks were created in JupyterLab. You cannot use the JupyterLab IDE in the project.

    You can download sample projects from Industry accelerators that contain a set of data science assets to accomplish a specific goal.

    You have these project configuration options:

    • Mark the project as sensitive. The project has a sensitive tag and project collaborators can't move data assets out of the project. You can enable or disable this option at any time on the project Settings page.
    • Log project activity. Detailed project activity is tracked in a full activities log that you can download. You can enable or disable this option at any time on the project Settings page.

  6. If you create a project with a Git repository, select the integration type:

  7. Click Create. You can start adding resources if your project is empty, or begin working with the assets and files you imported.

    Before you begin working with the imported assets, you should check for missing credentials, for example in notebooks and data connections, to enable successful relinking between the assets.

Next steps

Parent topic: Projects