Rule Sets define how data in a table and its columns should be masked, tokenized, or discovered during a compliance operation. A Rule Set acts as a container that organizes the data objects associated with a connector. After a connector is created, Rule Sets are used to select the tables or files that will be analyzed and processed during compliance workflows.

Each rule set is assigned a Purpose field that determines what type of compliance jobs can use it. The purpose can be either Mask or Tokenize. This field is immutable and cannot be changed after the rule set is created. The purpose affects which compliance job types can use the rule set:

  • Mask purpose: Can be used by Masking jobs and Discovery jobs

  • Tokenize purpose: Can be used by Tokenization jobs, Re-identification jobs, and Discovery jobs

Rule Sets store metadata about the selected objects, including table structures and column information. This metadata can be refreshed from the source system when schema changes occur.

For database columns, the is_nullable metadata indicates whether a column accepts null values. DCT prevents assigning an algorithm that can return null values to a column marked as non-nullable. For more information, see Edit table attributes in a rule set.

Rule sets are used during several operations, including:

  • Discovering sensitive data

  • Assigning data classes and algorithms

  • Executing compliance jobs

Each rule set is associated with a connector. Operations performed on a rule set use the Job Orchestrator and its compliance nodes to access the underlying data source.

You can perform the following operations:

Create a rule set

Create a rule set from CSV

Import a CSV file into a rule set

Create a rule set for flat data files

Create a rule set for semi-structured files

Edit a rule set

Edit masking rules in a rule set

Edit rule set tables

Edit table attributes in a rule set

Refresh a rule set

Rename a rule set

Delete a rule set

Last updated
Oct 8, 2026