Audit and feedback data can contain sensitive information, such as personally identifying information (PII), that you want to redact or hide from unauthorized users. Use Data Cloud Data Governance to protect sensitive data by setting up dynamic data masking and field-specific data exclusion policies. Grant access to the impacted Data 360 objects according to an access policy.
Permission Sets for Data Spaces
Apply permissions at the data space level. That way, only authorized users can view or query Einstein AI Audit and Feedback data.
For permission set access tiers, see Data 360 Standard Permission Sets.
- On the
defaultdata space, users with the Data Cloud Architect (formerly the Data Cloud Admin) permission set have access to all the data (by default). The Data Cloud Architect can grant data access to users with the Data Cloud User permission set. To define the scope for data space access, see the instructions in Assign a Data Space Permission Set to a Data Cloud User. - On a custom data space, only users with the Data Cloud Architect permission set have access to all the data.
Access Policy Options
You can select from either attribute-based access control (ABAC) or role-based access control (RBAC). Access control provides granular control over your users' access to data. Follow instructions in Assign Data Access to assign these objects to an available policy.
Impacted Data 360 Objects
For a list of impacted Data 360 objects, see Data Model for Generative AI Audit and Feedback.
If you have more than one data space, grant access to objects in each data space. Object
names in non-default data spaces follow the convention of <DataSpace
Prefix>_<Object Name>.
Test Your Access Policies
After you've updated permissions, be sure to test user access to collected audit and feedback data.