Export and delete in-product user data from Machine Learning Studio (classic)
APPLIES TO: Machine Learning Studio (classic) Azure Machine Learning
Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to Azure Machine Learning by that date.
Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.
- See information on moving machine learning projects from ML Studio (classic) to Azure Machine Learning.
- Learn more about Azure Machine Learning
ML Studio (classic) documentation is being retired and may not be updated in the future.
You can delete or export in-product data stored by Machine Learning Studio (classic) by using the Azure portal, the Studio (classic) interface, PowerShell, and authenticated REST APIs. This article tells you how.
Telemetry data can be accessed through the Azure Privacy portal.
For information about viewing or deleting personal data, see Azure Data Subject Requests for the GDPR. For more information about GDPR, see the GDPR section of the Microsoft Trust Center and the GDPR section of the Service Trust portal.
This article provides steps about how to delete personal data from the device or service and can be used to support your obligations under the GDPR. For general information about GDPR, see the GDPR section of the Microsoft Trust Center and the GDPR section of the Service Trust portal.
What kinds of user data does Studio (classic) collect?
For this service, user data consists of information about users authorized to access workspaces and telemetry records of user interactions with the service.
There are two kinds of user data in Machine Learning Studio (classic):
- Personal account data: Account IDs and email addresses associated with an account.
- Customer data: Data you uploaded to analyze.
Studio (classic) account types and how data is stored
There are three kinds of accounts in Machine Learning Studio (classic). The kind of account you have determines how your data is stored and how you can delete or export it.
- A guest workspace is a free, anonymous account. You sign up without providing credentials, such as an email address or password.
- Data is purged after the guest workspace expires.
- Guest users can export customer data through the UI, REST APIs, or PowerShell package.
- A free workspace is a free account you sign in to with Microsoft account credentials - an email address and password.
- You can export and delete personal and customer data, which are subject to data subject rights (DSR) requests.
- You can export customer data through the UI, REST APIs, or PowerShell package.
- For free workspaces not using Azure AD accounts, telemetry can be exported using the Privacy Portal.
- When you delete the workspace, you delete all personal customer data.
- A standard workspace is a paid account you access with sign-in credentials.
- You can export and delete personal and customer data, which are subject to DSR requests.
- You can access data through the Azure Privacy portal
- You can export personal and customer data through the UI, REST APIs, or PowerShell package
- You can delete your data in the Azure portal.
Delete workspace data in Studio (classic)
Delete individual assets
Users can delete assets in a workspace by selecting them, and then selecting the delete button.
Delete an entire workspace
Users can also delete their entire workspace:
- Paid workspace: Delete through the Azure portal.
- Free workspace: Use the delete button in the Settings pane.
Export Studio (classic) data with PowerShell
Use PowerShell to export all your information to a portable format from Machine Learning Studio (classic) using commands. For information, see the PowerShell module for Machine Learning Studio (classic) article.
For documentation covering web services and commitment plan billing, see Machine Learning Studio (classic) REST API reference.