A sensitive data model (SDM) is a collection of sensitive columns and referential relationships. Data Discovery identifies sensitive columns and referential relationships and creates an SDM. Data Discovery automatically searches the Oracle data dictionary to find parent-child relationships. It can also discover non-dictionary referential relationships, which are relationships defined in applications, but not in the Oracle data dictionary.
The Sensitive Data Models page in the Library lists the SDMs to which you have access. Metadata is also stored in an SDM, such as sample data, column count (the number of sensitive columns in the target database), and estimated data count (the number sensitive values). This information gives you a perspective on the quantity of the different types of sensitive data in your target databases.
You can perform incremental updates to an SDM during and after its creation. Incremental updating reruns the data discovery job and adds new sensitive columns to the sensitive data model. You can also manually add and remove sensitive columns from an SDM at any time.
Data Discovery provides a verification feature that enables you to verify that an SDM is valid for a target database. Verification checks whether the sensitive columns in the SDM are present on the selected target database. It identifies the sensitive columns that no longer exist in the target database but are present in the sensitive data model. Verification is useful when you mask sensitive data and need to verify that your SDM works against multiple target databases. To enable you to transfer SDMs from one Oracle Data Safe Library to another, you can download and upload file-based SDMs (XML files).