A data domain is an object that represents the functional meaning of a column based on the column data or the column name. Configure data domains to group data source columns for data masking. You can assign a masking rule to a data domain and all the columns in the data domain are masked with the same rule.
Create data domains to describe the columns you need to mask with the same masking rules. Assign at least one masking rule to each data domain.
For example, you might need to mask all the instances of Social Security number with the same masking rule. You can create a data domain that describes the Social Security data that occurs in the different columns. A database might have a Social Security number in a column called SSN. The database also has a column called SOCIAL_SECURITY in a different table. A Social Security number might also appear in a COMMENTS column.
When you create the data domain, you create a data expression that describes the data format for Social Security numbers. A Social Security number has this format:
. You can also create multiple metadata expressions that describe possible column names for Social Security numbers. Social Security column names might include
After you define a data domain, you can add the data domain to a policy. You can run profiles for data discovery against data sources in a project. Run profiles to find the columns for data domains. For example, the profile job can find all the Social Security numbers in the source data based on how you defined the data domain. The profile assigns data domains to columns.
If you do not have Data Discovery, you can still use data domains to aggregate data. However, you must manually associate source columns with the data domains.