Data Mask & Seed Requirements and Limitations

Requirements and Limitations

Before working with Data Mask & Seed, review the following requirements and limitations:

• Permissions and access
• Object masking constraints
• Custom library limits
• Masking job record and job concurrency caps

Permissions and Access

• To access and work with the new Data Mask & Seed application, assign users the following Permission Set License and Permission Set. Make sure to assign the Permission Set License before assigning the Permission Set:
  • Data Mask And Seed User Permission Set License
  • Data Mask and Seed User Permission Set
• To use the Create with Einstein option to generate custom library info entries, you must have Einstein enabled for your user, which requires your org to have an Einstein license. If your org has this license, either a Salesforce admin or you can enable Einstein for your user.

To enable Einstein for Data Mask & Seed:

• Verify that your org has an Einstein license.
• In the UI Setup menu, enter Data Mask in the Quick Find field.
• Select the Data Mask & Seed settings page.
• Enable Einstein for your user.

Object Masking

When you include the User object in a masking policy, Data Mask & Seed masks only the following types of users:

• PowerCustomerSuccess
• CustomerSuccess
• CspLitePortal

Custom Libraries

When using Salesforce’s Einstein utility to generate info entries for custom libraries, each Einstein generation of info entries is limited to a maximum of 100 entries.

Masking Job Processing

Record Limits

• When a masking job exceeds 20,000,000 records, Data Mask & Seed runs the job, however:
  • The app doesn't preserve existing data distributions in the sandbox. This means that the app doesn't analyze the distribution of field values within an object's records during a sandbox masking job. Therefore, masking doesn't preserve the original frequency and proportion of field values across the records of each object
  • The app doesn't apply consistent field masking across objects. This means that the app doesn't apply the same masking value to identical fields that are found across multiple objects in your masking policy
• Per masking job, Data Mask & Seed supports masking a maximum of 350,000,000 records. At a job's outset, Data Mask & Seed first counts the candidate records to be masked to determine whether or not the job exceeds the maximum record limit. If the job exceeds this limit, Data Mask & Seed cancels the job, doesn't perform any masking and records an error message in the Masking Job Report.

Note If your masking job exceeds the maximum record limit, reduce the job's total number of records by either removing objects from the masking policy, applying object record filters in the masking policy, or the combined use of both approaches.

Concurrency Limit

• Per sandbox, Data Mask & Seed supports running a maximum of 12 masking jobs during the current 24-hour rolling window. When a sandbox exceeds this limit, new jobs are cancelled and an error message is recorded in the Masking Job Report of each cancelled job.

Bypassing Automations Limitations

Data Mask and Seed doesn't bypass automations when deleting records in the following scenarios:

• When deleting the Feed Items and History records of masked sandbox objects, during a masking job
• When deleting PII-containing records for each one of three different sandbox objects - Case Comments, Email Messages, and Chatter Comments, as initiated by the user from the the Associated PII section of the Data Mask & Seed Home page

Also, Data Mask & Seed doesn't bypass the Duplicate Detection automation. Therefore, duplicates may be created, unless the user manually disables the automation before the masking job (and should re-enable the automation, after the masking job completes).

Related Topics

After reviewing these Data Mask & Seed requirements and limitations, you can begin working with the app:

• To create and edit masking policies, see Create a Masking Policy and the Policies Tab
• To create and edit custom libraries, see Custom Libraries Overview
• Once you have created a masking policy that suits your masking needs, do any of the following:
  • Manually run a masking job using that policy, see Run a Masking Job
  • Schedule masking jobs to be automatically run using that policy, see Schedule a Masking Policy
• While a masking job is in progress or after the job completes, you can view the job's current status or review the completed job's results, see the Jobs Tab