Author a Masking Data Policy

1. Determine your policy scope:
   • Global policy: Click the Policies page icon in the left sidebar and select the Data Policies tab. Click Add Policy and enter a name for your policy.
   • Local policy: Navigate to a specific data source and click the Policies tab. Scroll to the Data Policies section and click Add Policy.

2. Select Mask from the first dropdown menu.

3. Select columns tagged, columns with any tag, columns with no tags, all columns, or columns with names spelled like.

4. Select a masking type:

   • using hashing
   • with reversibility
   • by making null
   • using a constant: Enter a constant in the field that appears next to the masking type dropdown.
   • using a regex:
     1. Enter a regular expression and replacement value in the fields that appear next to the masking type dropdown.
     2. From the next dropdown, choose to make the regex Case Insensitive and/or Global.

   • by rounding:

     1. Select using fingerprint or specifying the bucket from the subsequent dropdown menu.
     2. If specifying the bucket, select the Bucket Type and then enter the bucket size.

     Note: If you choose by rounding as your masking type, the statistics of the data fingerprint will autogenerate the bucket size when the policy is applied to a data source.

   • with format preserving masking

   • with K-Anonymization: Select either using fingerprint or requiring group size of at least and enter a group size in the subsequent dropdown menu.
   • using randomized response

   • using the custom function: Enter the custom function native to the underlying database.

     Note: The function must be valid for the data type of the column. If it is not, the default masking type will be applied to the column.

5. Select everyone except, everyone, or everyone who to continue the condition.

   • everyone except: In the subsequent dropdown menus, choose is a member of group, possesses attribute, or is acting under purpose. Complete the condition with the subsequent dropdown menus.
   • for everyone who: Complete the Otherwise clause. You can add more than one condition by selecting + Add Another Condition. The dropdown menu in the policy builder contains conjunctions for your policy. If you select or, only one of your conditions must apply to a user for them to see the data. If you select and, all of the conditions must apply.

6. Opt to complete the Enter Rationale for Policy (Optional) field, and then click Add.

7. For global policies: Click the dropdown menu beneath Where should this policy be applied and select When selected by data owners, On all data sources, or On data sources. If you selected On data sources, finish the condition in one of the following ways:

   • tagged: Select this option and then search for tags in the subsequent dropdown menu.

   • with columns tagged: Select this option and then search for tags in the subsequent dropdown menu.

   • with column names spelled like: Select this option, and then enter a regex and choose a modifier in the subsequent fields.

   • in server: Select this option and then choose a server from the subsequent dropdown menu to apply the policy to data sources that share this connection string.

   • created between: Select this option and then choose a start date and an end date in the subsequent dropdown menus.

8. Click Create Policy. If creating a global policy, you then need to click Activate Policy or Stage Policy.

Create a custom certification for a global policy

This step is optional, but data governors can add certifications that outline acknowledgements or require approvals from data owners. For example, data governors could add a custom certification that states that data owners must verify that tags have been added correctly to their data sources before certifying the policy.

1. Click Add Certification in the data policy builder.

2. Enter a Certification Label and Certification Text in the corresponding fields of the dialog that appears.

3. Click Save.