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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
  • Selecting and configuring tables
  • Selecting the table to view
  • Selecting the table mode
  • Viewing the generator configuration summary
  • Changing the column data display
  • Toggling between source and preview data
  • Using a query to filter the source data
  • Information in the column headings
  • Primary and foreign key indicators
  • Protection status
  • Sensitivity confidence
  • Column data type
  • Child workspace overrides
  • Configuring a column
  • Applying or ignoring a recommended generator
  • Changing the column generator configuration
  • Indicating whether a column is sensitive
  • Enabling Document View for file connector JSON columns

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  1. Configuring data generation

Table View

Last updated 3 days ago

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Table View displays source or preview data for a single table. For a workspace, each table corresponds to a file group.

Required workspace permission:

  • Source data: Preview source data

  • Destination data: Preview destination data

If you do not have either of these permissions, then you cannot display Table View.

To display Table View:

  • On the workspace management view, click Table View.

  • On Workspaces view, from the dropdown menu in the Name column, select Table View.

  • From Database View, either click the arrow icon for the table, or click a row in the table.

From Table View, you can view and update the table and column configuration.

Selecting and configuring tables

Selecting the table to view

When you display Table View from Database View, it displays the data for the selected table.

When you display Table View from the workspace management view or Workspaces view, it displays the most recently displayed table.

If Table View was never displayed before, then it displays the first table in the workspace.

To change the selected table, from the Table dropdown list, select the table to view.

Selecting the table mode

Required workspace permission: Assign table modes

To change the table mode that is assigned to the table:

  1. Click the current table mode.

  2. On the table mode panel, from the table mode dropdown list, select the new table mode.

When you change the table mode, Tonic Structural updates the preview data as needed. For example, if you change the table mode to Truncate, then the preview data is empty.

If the child workspace currently overrides the parent workspace configuration, then to reset the table mode to the table that is assigned in the parent workspace, click Reset.

Viewing the generator configuration summary

The Model section of Table View displays the configured generators for the table columns.

The header for each Model entry is the column name.

Linked columns share an entry. The heading is a comma-separated list of the linked columns.

Each entry contains the following information:

  • The column and generator, in the format Column Name >> Generator Name. For example, First_Name >> Name indicates that the First_Name column has the Name generator applied. For linked columns, there is a Column Name >> Generator Name entry for each column.

  • The selected configuration options for the generator.

To remove the generator from a column, click the delete icon.

Changing the column data display

Toggling between source and preview data

The Preview toggle at the top right of Table View allows you to choose whether to display original source data or the transformed data. You can switch back and forth to understand exactly how Structural transforms the data based on the table and column configuration.

By default, the Preview toggle is in the on position, and the displayed data reflects the selected table mode and the assigned generators. For tables that use Truncate mode, the preview data is empty. Truncated tables do not have data in the destination database.

To display the original source data, toggle Preview to the off position.

Using a query to filter the source data

You can provide a query to filter the source data. The query is always against the source data, not the preview data, regardless of whether the Preview toggle is off or on.

For example, you configure a first name field to use the Name generator and enable consistency. You can then query the source data for a specific first name value to check that the preview data uses the same destination value for all of those records.

To apply a query to the source data:

  1. Click the query filter icon, located between the table name and the table mode.

  2. On the Table Filter dialog, provide the WHERE clause for the query.

  3. To apply the query, click Apply.

  4. To close the dialog, click Close.

To clear an applied query, on the Table Filter dialog, click Clear.

If no filter is applied, then the query filter icon has a white background.

If a valid filter is applied, then the query filter icon has a gray background.

If the provided WHERE clause is not valid, then the query filter icon has a red background.

Information in the column headings

In addition to the column name, the column heading provides details about the column type and protection status. It also provides access to change the column configuration.

Primary and foreign key indicators

The column heading indicates when a column is either a primary key or a foreign key.

Protection status

The column heading indicates the column protection status:

  • At risk columns are sensitive and do not have an assigned generator.

  • Protected columns have an assigned generator.

  • Not sensitive columns are not sensitive and do not have an assigned generator.

Sensitivity confidence

The sensitivity confidence indicator indicates the confidence in the detection.

For sensitive columns that Structural detected, the confidence level can be high, medium, or low.

For custom sensitivity rule matches or columns that you manually marked as sensitive, the confidence level is full confidence.

Column data type

The column heading displays the type of data that the column contains.

Child workspace overrides

Required license: Enterprise

To filter Table View to only display columns with overrides, toggle Show Overrides Only to the on position.

Configuring a column

Applying or ignoring a recommended generator

Required workspace permission: Configure column generators

When a sensitivity scan identifies a column, Structural recommends a generator for the column. For example, when the sensitivity scan identifies a column as a first name, Structural recommends the Name generator configured to generate a first name value.

For unprotected columns that have a recommended generator, the column heading displays the available recommendation icon.

To review and either apply or ignore the recommended generator, click the generator dropdown.

The generator recommendation panel contains the following information:

  • The sensitivity confidence level

  • The recommended generator

  • Sample source and destination values based on the recommended generator

From the panel, you choose whether to assign or ignore the recommended generator for that type.

  • To assign the recommended generator, click Apply. Structural displays the generator configuration panel with the recommended generator selected. You can then adjust the configuration or select a different generator.

  • To ignore the recommendation, click Ignore. Structural displays the generator configuration panel to allow you to select the generator to assign to the column.

Changing the column generator configuration

Required workspace permission: Configure column generators

To assign a generator to a column that does not have an assigned generator, or to change the current configuration, click the dropdown in the column heading.

On the generator configuration panel, from the generator type dropdown list, select the generator to assign to the column.

Structural displays the available configuration options for the selected generator. For details about the configuration options for each generator, go to the Generator reference.

To remove the selected generator or generator preset, and reset the generator to Passthrough, click the delete icon next to the generator.

For more information about selecting and configuring generators and generator presets, go to Assigning and configuring generators.

Indicating whether a column is sensitive

Required workspace permission: Configure column sensitivity

On the column configuration panel, the Sensitive Data toggle indicates whether the column is marked as sensitive. The initial configuration is based on the sensitivity scan.

  • To mark a column as sensitive, toggle the setting to the on position.

  • To mark a column as not sensitive, toggle the setting to the off position.

When you copy a workspace, Structural performs a new sensitivity scan on the copy. It does not copy the sensitivity designations from the original workspace.

Enabling Document View for file connector JSON columns

For a file connector JSON column, instead of assigning a generator, you can enable Document View.

From Document View, you can view the JSON schema structure and assign generators to individual JSON fields. For more information, go to Document View for file connector JSON columns.

When Document View is enabled, the generator dropdown is replaced with the Open in Document View option.

For a , the table mode selection panel indicates whether the selected table mode is inherited from the parent workspace.

For a , each Model entry indicates whether the configuration overrides the parent configuration. For configurations that override the parent, to remove the overrides and restore the inheritance, click Reset.

The Model entry also indicates when is enabled for the column.

Note that for , you cannot preview the destination data from Table View. You must preview the data from Document View.

For more information about how Structural identifies values and assigns the confidence level, go to .

In a , when a column overrides the parent configuration, an Overriding label displays in the column heading.

In a , you cannot configure whether a column is sensitive. A child workspace always inherits the sensitivity designation from its parent workspace.

To enable Document View, on the column configuration panel, toggle Use Document View to the on position. Note that if you have , or enabled , then the Use Document View toggle is in the advanced options.

child workspace
child workspace
Structural data encryption
child workspace
child workspace
custom value processors
Structural data encryption
JSON columns that use Document View
file connector
Table View with highlighted sections
Table Mode selection on Table View
Table mode configuration that overrides the parent workspace
Model section of Table View
Model entry for linked columns
Model entry for a configuration that overrides the parent workspace
Table Filter dialog for Table View
Query filter icon when no query is applied
Query filter icon when a query is applied
Query filter icon when a bad query is applied
Column headings for primary and foreign keys
Protection status indicators in the column headings
Sensitivity confidence level indicator
Data type information in the column headings
Table View column with a configuration override
Table View with Show Overrides Only enabled
Table View column heading with the recommended generator icon
Recommended generator panel for a column on Table View
Generator dropdown list for a Table View column
How Structural identifies sensitive values