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  • Tonic Structural User Guide
  • About Tonic Structural
    • Structural data generation workflow
    • Structural deployment types
    • Structural implementation roles
    • Structural license plans
  • Logging into Structural for the first time
  • Getting started with the Structural free trial
  • Managing your user account
  • Frequently Asked Questions
  • Tutorial videos
  • Creating and managing workspaces
    • Managing workspaces
      • Viewing your list of workspaces
      • Creating, editing, or deleting a workspace
      • Workspace configuration settings
        • Workspace identification and connection type
        • Data connection settings
        • Configuring secrets managers for database connections
        • Data generation settings
        • Enabling and configuring upsert
        • Writing output to Tonic Ephemeral
        • Writing output to a container repository
        • Advanced workspace overrides
      • About the workspace management view
      • About workspace inheritance
      • Assigning tags to a workspace
      • Exporting and importing the workspace configuration
    • Managing access to workspaces
      • Sharing workspace access
      • Transferring ownership of a workspace
    • Viewing workspace jobs and job details
  • Configuring data generation
    • Privacy Hub
    • Database View
      • Viewing and configuring tables
      • Viewing the column list
      • Displaying sample data for a column
      • Configuring an individual column
      • Configuring multiple columns
      • Identifying similar columns
      • Commenting on columns
    • Table View
    • Working with document-based data
      • Performing scans on collections
      • Using Collection View
    • Identifying sensitive data
      • Running the Structural sensitivity scan
      • Manually indicating whether a column is sensitive
      • Built-in sensitivity types that Structural detects
      • Creating and managing custom sensitivity rules
    • Table modes
    • Generator information
      • Generator summary
      • Generator reference
        • Address
        • Algebraic
        • Alphanumeric String Key
        • Array Character Scramble
        • Array JSON Mask
        • Array Regex Mask
        • ASCII Key
        • Business Name
        • Categorical
        • Character Scramble
        • Character Substitution
        • Company Name
        • Conditional
        • Constant
        • Continuous
        • Cross Table Sum
        • CSV Mask
        • Custom Categorical
        • Date Truncation
        • Email
        • Event Timestamps
        • File Name
        • Find and Replace
        • FNR
        • Geo
        • HIPAA Address
        • Hostname
        • HStore Mask
        • HTML Mask
        • Integer Key
        • International Address
        • IP Address
        • JSON Mask
        • MAC Address
        • Mongo ObjectId Key
        • Name
        • Noise Generator
        • Null
        • Numeric String Key
        • Passthrough
        • Phone
        • Random Boolean
        • Random Double
        • Random Hash
        • Random Integer
        • Random Timestamp
        • Random UUID
        • Regex Mask
        • Sequential Integer
        • Shipping Container
        • SIN
        • SSN
        • Struct Mask
        • Timestamp Shift Generator
        • Unique Email
        • URL
        • UUID Key
        • XML Mask
      • Generator characteristics
        • Enabling consistency
        • Linking generators
        • Differential privacy
        • Partitioning a column
        • Data-free generators
        • Supporting uniqueness constraints
        • Format-preserving encryption (FPE)
      • Generator types
        • Composite generators
        • Primary key generators
    • Generator assignment and configuration
      • Reviewing and applying recommended generators
      • Assigning and configuring generators
      • Document View for file connector JSON columns
      • Generator hints and tips
      • Managing generator presets
      • Configuring and using Structural data encryption
      • Custom value processors
    • Subsetting data
      • About subsetting
      • Using table filtering for data warehouses and Spark-based data connectors
      • Viewing the current subsetting configuration
      • Subsetting and foreign keys
      • Configuring subsetting
      • Viewing and managing configuration inheritance
      • Viewing the subset creation steps
      • Viewing previous subsetting data generation runs
      • Generating cohesive subset data from related databases
      • Other subsetting hints and tips
    • Viewing and adding foreign keys
    • Viewing and resolving schema changes
    • Tracking changes to workspaces, generator presets, and sensitivity rules
    • Using the Privacy Report to verify data protection
  • Running data generation
    • Running data generation jobs
      • Types of data generation
      • Data generation process
      • Running data generation manually
      • Scheduling data generation
      • Issues that prevent data generation
    • Managing data generation performance
    • Viewing and downloading container artifacts
    • Post-job scripts
    • Webhooks
  • Installing and Administering Structural
    • Structural architecture
    • Using Structural securely
    • Deploying a self-hosted Structural instance
      • Deployment checklist
      • System requirements
      • Deploying with Docker Compose
      • Deploying on Kubernetes with Helm
      • Enabling the option to write output data to a container repository
        • Setting up a Kubernetes cluster to use to write output data to a container repository
        • Required access to write destination data to a container repository
      • Entering and updating your license key
      • Setting up host integration
      • Working with the application database
      • Setting up a secret
      • Setting a custom certificate
    • Using Structural Cloud
      • Structural Cloud notes
      • Setting up and managing a Structural Cloud pay-as-you-go subscription
      • Structural Cloud onboarding
    • Managing user access to Structural
      • Structural organizations
      • Determining whether users can create accounts
      • Creating a new account in an existing organization
      • Single sign-on (SSO)
        • Structural user authentication with SSO
        • Enabling and configuring SSO on Structural Cloud
        • Synchronizing SSO groups with Structural
        • Viewing the list of SSO groups in Tonic Structural
        • AWS IAM Identity Center
        • Duo
        • GitHub
        • Google
        • Keycloak
        • Microsoft Entra ID (previously Azure Active Directory)
        • Okta
        • OpenID Connect (OIDC)
        • SAML
      • Managing Structural users
      • Managing permissions
        • About permission sets
        • Built-in permission sets
        • Available permissions
        • Viewing the lists of global and workspace permission sets
        • Configuring custom permission sets
        • Selecting default permission sets
        • Configuring access to global permission sets
        • Setting initial access to all global permissions
        • Granting Account Admin access for a Structural Cloud organization
    • Structural monitoring and logging
      • Monitoring Structural services
      • Performing health checks
      • Downloading the usage report
      • Tracking user access and permissions
      • Redacted and diagnostic (unredacted) logs
      • Data that Tonic.ai collects
      • Verifying and enabling telemetry sharing
    • Configuring environment settings
    • Updating Structural
  • Connecting to your data
    • About data connectors
    • Overview for database administrators
    • Data connector summary
    • Amazon DynamoDB
      • System requirements and limitations for DynamoDB
      • Structural differences and limitations with DynamoDB
      • Before you create a DynamoDB workspace
      • Configuring DynamoDB workspace data connections
    • Amazon EMR
      • Structural process overview for Amazon EMR
      • System requirements for Amazon EMR
      • Structural differences and limitations with Amazon EMR
      • Before you create an Amazon EMR workspace
        • Creating IAM roles for Structural and Amazon EMR
        • Creating Athena workgroups
        • Configuration for cross-account setups
      • Configuring Amazon EMR workspace data connections
    • Amazon Redshift
      • Structural process overview for Amazon Redshift
      • Structural differences and limitations with Amazon Redshift
      • Before you create an Amazon Redshift workspace
        • Required AWS instance profile permissions for Amazon Redshift
        • Setting up the AWS Lambda role for Amazon Redshift
        • AWS KMS permissions for Amazon SQS message encryption
        • Amazon Redshift-specific Structural environment settings
        • Source and destination database permissions for Amazon Redshift
      • Configuring Amazon Redshift workspace data connections
    • Databricks
      • Structural process overview for Databricks
      • System requirements for Databricks
      • Structural differences and limitations with Databricks
      • Before you create a Databricks workspace
        • Granting access to storage
        • Setting up your Databricks cluster
        • Configuring the destination database schema creation
      • Configuring Databricks workspace data connections
    • Db2 for LUW
      • System requirements for Db2 for LUW
      • Structural differences and limitations with Db2 for LUW
      • Before you create a Db2 for LUW workspace
      • Configuring Db2 for LUW workspace data connections
    • File connector
      • Overview of the file connector process
      • Supported file and content types
      • Structural differences and limitations with the file connector
      • Before you create a file connector workspace
      • Configuring the file connector storage type and output options
      • Managing file groups in a file connector workspace
      • Downloading generated file connector files
    • Google BigQuery
      • Structural differences and limitations with Google BigQuery
      • Before you create a Google BigQuery workspace
      • Configuring Google BigQuery workspace data connections
      • Resolving schema changes for de-identified views
    • MongoDB
      • System requirements for MongoDB
      • Structural differences and limitations with MongoDB
      • Configuring MongoDB workspace data connections
      • Other MongoDB hints and tips
    • MySQL
      • System requirements for MySQL
      • Before you create a MySQL workspace
      • Configuring MySQL workspace data connections
    • Oracle
      • Known limitations for Oracle schema objects
      • System requirements for Oracle
      • Structural differences and limitations with Oracle
      • Before you create an Oracle workspace
      • Configuring Oracle workspace data connections
    • PostgreSQL
      • System requirements for PostgreSQL
      • Before you create a PostgreSQL workspace
      • Configuring PostgreSQL workspace data connections
    • Salesforce
      • System requirements for Salesforce
      • Structural differences and limitations with Salesforce
      • Before you create a Salesforce workspace
      • Configuring Salesforce workspace data connections
    • Snowflake on AWS
      • Structural process overviews for Snowflake on AWS
      • Structural differences and limitations with Snowflake on AWS
      • Before you create a Snowflake on AWS workspace
        • Required AWS instance profile permissions for Snowflake on AWS
        • Other configuration for Lambda processing
        • Source and destination database permissions for Snowflake on AWS
        • Configuring whether Structural creates the Snowflake on AWS destination database schema
      • Configuring Snowflake on AWS workspace data connections
    • Snowflake on Azure
      • Structural process overview for Snowflake on Azure
      • Structural differences and limitations with Snowflake on Azure
      • Before you create a Snowflake on Azure workspace
      • Configuring Snowflake on Azure workspace data connections
    • Spark SDK
      • Structural process overview for the Spark SDK
      • Structural differences and limitations with the Spark SDK
      • Configuring Spark SDK workspace data connections
      • Using Spark to run de-identification of the data
    • SQL Server
      • System requirements for SQL Server
      • Before you create a SQL Server workspace
      • Configuring SQL Server workspace data connections
    • Yugabyte
      • System requirements for Yugabyte
      • Structural differences and limitations with Yugabyte
      • Before you create a Yugabyte workspace
      • Configuring Yugabyte workspace data connections
      • Troubleshooting Yugabyte data generation issues
  • Using the Structural API
    • About the Structural API
    • Getting an API token
    • Getting the workspace ID
    • Using the Structural API to perform tasks
      • Configure environment settings
      • Manage generator presets
        • Retrieving the list of generator presets
        • Structure of a generator preset
        • Creating a custom generator preset
        • Updating an existing generator preset
        • Deleting a generator preset
      • Manage custom sensitivity rules
      • Create a workspace
      • Connect to source and destination data
      • Manage file groups in a file connector workspace
      • Assign table modes and filters to source database tables
      • Set column sensitivity
      • Assign generators to columns
        • Getting the generator IDs and available metadata
        • Updating generator configurations
        • Structure of a generator assignment
        • Generator API reference
          • Address (AddressGenerator)
          • Algebraic (AlgebraicGenerator)
          • Alphanumeric String Key (AlphaNumericPkGenerator)
          • Array Character Scramble (ArrayTextMaskGenerator)
          • Array JSON Mask (ArrayJsonMaskGenerator)
          • Array Regex Mask (ArrayRegexMaskGenerator)
          • ASCII Key (AsciiPkGenerator)
          • Business Name (BusinessNameGenerator)
          • Categorical (CategoricalGenerator)
          • Character Scramble (TextMaskGenerator)
          • Character Substitution (StringMaskGenerator)
          • Company Name (CompanyNameGenerator)
          • Conditional (ConditionalGenerator)
          • Constant (ConstantGenerator)
          • Continuous (GaussianGenerator)
          • Cross Table Sum (CrossTableAggregateGenerator)
          • CSV Mask (CsvMaskGenerator)
          • Custom Categorical (CustomCategoricalGenerator)
          • Date Truncation (DateTruncationGenerator)
          • Email (EmailGenerator)
          • Event Timestamps (EventGenerator)
          • File Name (FileNameGenerator)
          • Find and Replace (FindAndReplaceGenerator)
          • FNR (FnrGenerator)
          • Geo (GeoGenerator)
          • HIPAA Address (HipaaAddressGenerator)
          • Hostname (HostnameGenerator)
          • HStore Mask (HStoreMaskGenerator)
          • HTML Mask (HtmlMaskGenerator)
          • Integer Key (IntegerPkGenerator)
          • International Address (InternationalAddressGenerator)
          • IP Address (IPAddressGenerator)
          • JSON Mask (JsonMaskGenerator)
          • MAC Address (MACAddressGenerator)
          • Mongo ObjectId Key (ObjectIdPkGenerator)
          • Name (NameGenerator)
          • Noise Generator (NoiseGenerator)
          • Null (NullGenerator)
          • Numeric String Key (NumericStringPkGenerator)
          • Passthrough (PassthroughGenerator)
          • Phone (USPhoneNumberGenerator)
          • Random Boolean (RandomBooleanGenerator)
          • Random Double (RandomDoubleGenerator)
          • Random Hash (RandomStringGenerator)
          • Random Integer (RandomIntegerGenerator)
          • Random Timestamp (RandomTimestampGenerator)
          • Random UUID (UUIDGenerator)
          • Regex Mask (RegexMaskGenerator)
          • Sequential Integer (UniqueIntegerGenerator)
          • Shipping Container (ShippingContainerGenerator)
          • SIN (SINGenerator)
          • SSN (SsnGenerator)
          • Struct Mask (StructMaskGenerator)
          • Timestamp Shift (TimestampShiftGenerator)
          • Unique Email (UniqueEmailGenerator)
          • URL (UrlGenerator)
          • UUID Key (UuidPkGenerator)
          • XML Mask (XmlMaskGenerator)
      • Configure subsetting
      • Check for and resolve schema changes
      • Run data generation jobs
      • Schedule data generation jobs
    • Example script: Starting a data generation job
    • Example script: Polling for a job status and creating a Docker package
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On this page
  • Viewing the list of presets
  • Information in the generator presets list
  • Filtering the generator preset list
  • Sorting the generator preset list
  • Configuring generator presets
  • Creating a custom generator preset
  • Updating a generator preset
  • Configuration options for generator presets
  • Viewing generator preset occurrences
  • Deleting a custom generator preset

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  1. Configuring data generation
  2. Generator assignment and configuration

Managing generator presets

Last updated 1 month ago

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Required license: Professional

On Basic or Professional instances, you select and configure generators separately for each column.

Required global permission: Create and manage generator presets

A generator preset is a saved configuration for a generator.

Tonic Structural provides a built-in preset for every generator. You can update the configuration of the built-in presets.

You can also create custom generator presets that have different configurations. For example, for the Address generator, you can have one generator preset to use for city columns, and another generator preset to use for full addresses.

You can edit and delete custom generator presets. The custom generator presets are available to assign to columns throughout the Structural instance.

Generator presets allow you to standardize the configuration for generators, and saves your users from having to replicate the same configuration selections across different columns, tables, and workspaces. For example, you might modify the generator preset for the Integer Key generator to enable consistency. Whenever a user assigns the Integer Key generator to a column, consistency is enabled.

For information about assigning and updating generator presets for a column, go to Assigning and configuring generators.

You can also view the .

Viewing the list of presets

The Generator Presets view contains the list of generator presets for a self-hosted Structural instance or a user's Structural Cloud organization. The configured presets are not specific to a workspace or a user.

To display the Generator Presets view, in the Structural heading, click Generator Presets.

Information in the generator presets list

For each generator preset, the list provides the following information:

  • The name of the generator preset. For the built-in presets, the generator preset name always matches the generator name.

  • Whether the generator preset is built-in or custom.

  • The number of occurrences. Includes the number of occurrences that use the current baseline configuration, and the number of occurrences that have overrides to the baseline configuration.

    An occurrence has an override if, after a user assigns the generator preset to a column, one the following occurs:

    • A user changes the generator configuration options for that occurrence.

    • A user changes the baseline configuration for the generator preset.

  • When the preset configuration was most recently modified.

You cannot create or configure generator presets for generators that do not have any configuration options. For example, the Null generator does not have any configuration options.

For composite generators, you cannot create or configure generator presets from Generator Presets view. Generator Presets does not have access to data from which to create path expressions. You can create a new preset or update a preset baseline configuration from a column configuration panel in Privacy Hub, Database View, or Table View.

The list indicates when a generator does not allow you to configure presets.

Filtering the generator preset list

You can filter the list of generator presets by the preset name, whether it is built-in or custom, and by the underlying generator type.

Filtering by preset name

To filter by the preset name, begin to type text from the name. As you type, Structural filters the list to only include the matching presets.

Filtering by preset type (built-in or custom)

To filter the list based on whether the preset is built-in or custom:

  1. Click Filter by Type.

  2. In the dropdown list: To only include built-in presets, click Built-in. To only include custom presets, click Custom.

Structural adds the selection to the selected filters.

Filtering by generator type

Every generator preset is based on a Structural generator type. For example, there is a built-in generator preset for the Address generator, and you can also create custom generator presets based on the Address generator.

To filter the list based on the generator type:

  1. Click Filter by Generator.

  2. In the generator list, click a generator to include. You can use the search field to search for a specific generator. When you click the generator name, Structural adds the generator to the selected filters.

Sorting the generator preset list

You can sort the generator preset list by the preset name and the by the modification date.

To sort the generator preset list by a column, click the column heading. To reverse the sort order, click the column heading again.

Configuring generator presets

Creating a custom generator preset

To create a new custom generator preset, you can either create a completely new preset, or copy an existing preset.

For composite generators such as JSON Mask, you cannot create a generator preset from Generator Presets view. Generator Presets view does not have access to data to use for path expressions. You can create presets for composite generators from a column configuration panel in Privacy Hub, Database View, or Table View.

You cannot create a custom preset at all for a generator that has no configuration options. For example, you cannot create a custom preset for the Null generator.

Creating a completely new custom generator preset

To create a completely new custom generator preset:

  1. On the Generator Presets view, click Create Preset.

  2. On the Create Preset panel, configure the generator preset.

  3. Click Create.

Copying an existing generator preset

When you copy an existing generator preset, the new generator preset by default inherits the configuration from the copied generator preset.

To copy an existing generator preset:

  1. On the Generator Presets view, click the copy icon for the generator preset that you want to copy.

  2. On the Copy Preset dialog, enter a name for the new generator preset, then click Copy. The new preset is added to the Generator Presets list, and the details panel is displayed to allow you to change the new preset configuration.

  3. After you update the configuration, click Save and Apply.

  4. On the confirmation panel, click Confirm.

Updating a generator preset

To edit a preset, you must be either an editor or owner of at least one workspace in the Structural instance or organization. If you are not an editor or owner of a workspace, then you can view the list of presets, but you cannot edit the presets.

When you change the configuration of a generator preset, the updated configuration becomes the new baseline configuration for the generator preset.

The baseline configuration is used whenever you select the generator preset. Existing occurrences of the generator preset keep their current configuration. You can then reset those occurrences to use the current baseline configuration.

A change to the generator preset description is not considered a change to the baseline configuration.

For composite generators such as JSON Mask, you cannot update a generator preset from Generator Presets view. Generator Presets view does not have access to data to use for path expressions. You can update the baseline configuration from a column configuration panel in Privacy Hub, Database View, or Table View.

To update the baseline configuration of a generator preset:

  1. On the Generator Presets view, click the edit icon for the preset.

  2. On the Configuration tab of the Edit Preset panel, update the configuration. You cannot change the selected generator for the preset.

  1. Click Save and Apply.

  2. On the confirmation panel, click Confirm.

Configuration options for generator presets

Each generator preset includes the following configuration:

  • Preset Name - The name of the generator preset. You cannot change the name of built-in presets. Built-in presets always use the generator name.

  • Preset Description - A longer description of the generator preset and how it is intended to be used.

  • Generator Type - Used to select the generator for a new generator preset. When you copy or edit a generator preset, you cannot change the selected generator.

  • Generator configuration - The configuration options for the selected generator. For details on the specific configuration options for each generator, go to the Generator reference.

The following options are not included in the generator preset configuration. You always configure these options for individual columns after you select the generator preset:

Viewing generator preset occurrences

On the generator preset details panel, the Occurrences tab indicates where the generator preset is used. You can also see whether each occurrence overrides the current baseline configuration.

The Occurrences tab displays the list of workspaces that contain occurrences of the preset. Each workspace indicates the total number of occurrences that use the current baseline configuration, and the number of occurrences that have overrides to the current baseline configuration.

For workspaces that you have access to:

  • You can expand the workspace to display the list of columns that use the generator preset. For each column, the entry indicates whether the column uses the current baseline configuration.

  • You can click the Database View icon to navigate to Database View.

For workspaces that you do not have access to, you can only see the total number of occurrences. You cannot display the column list or navigate to Database View.

Deleting a custom generator preset

You can delete custom generator presets. You cannot delete built-in generator presets.

When you delete a custom generator preset, existing occurrences are assigned the built-in generator preset for that generator. If the current configuration does not match the baseline configuration for the built-in generator preset, then Structural also marks the occurrences as having overrides.

For example, a column is assigned a custom generator preset for the Name generator. The custom generator preset is deleted. The column is then assigned the built-in generator preset for the Name generator, and is marked as having overrides.

To delete a custom generator preset:

  1. On the Generator Presets view, click the delete icon for the generator preset.

  2. On the confirmation dialog, click Delete Preset.

Linking
Consistency with another column
Partitioning
Custom value processors
video tutorial about generator presets
Generator Presets view
Generator Presets view with a name filter applied
Generator presets filter by filter type
Generator presets filter by generator type
Occurrences tab
Workspace occurrence details for a generator preset