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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
  • Column - Column name and type
  • Status - Protection and sensitivity status
  • Applied Generator - Column configuration
  • Filtering the column list
  • Filter by table
  • Filter by table or column name
  • Using the Filters panel
  • Filters panel filters
  • Columns with generator recommendations
  • At-risk columns
  • Sensitivity
  • Protection status
  • Inclusion in the destination database
  • Assigned generator
  • Column data type
  • Unresolved schema changes
  • Sensitivity type
  • Sensitivity confidence
  • Column nullability
  • Column uniqueness
  • Primary or foreign keys
  • Generator overrides in a child workspace
  • Uses Structural data encryption
  • Sorting the column list

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  1. Configuring data generation
  2. Database View

Viewing the column list

Last updated 1 month ago

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The column list on Database View contains information about the sensitivity and generator configuration for each column.

Column - Column name and type

The Column column provides general information about the columns and their content, including:

  • The name of the schema that contains the table.

  • The data type for the column.

  • An indicator when the column is a primary key

Status - Protection and sensitivity status

The Status column provides information about whether the column contains sensitive data and whether it has an assigned generator.

The protection status can be one of the following values:

  • Protected - The column has an assigned generator.

  • Not Sensitive - The column is marked as not sensitive.

  • At Risk - The column is sensitive and does not have an assigned generator.

At the right of the Status column is a confidence indicator. For At Risk columns, the confidence indicator shows how confident Structural is that the column is sensitive and contains values of the displayed sensitivity type. Protected columns also reflect the original confidence level.

Applied Generator - Column configuration

The generator dropdown indicates the currently assigned generator. It also indicates when an unprotected column has a recommended generator.

For foreign key columns, the generator dropdown is disabled and the column is marked as a foreign key. Foreign key columns always inherit the generator that is assigned to the primary key.

In a child workspace, when the generator configuration overrides the parent workspace, the generator dropdown displays the override icon.

Filtering the column list

To filter the column list, you can:

  • Use the table list to filter the displayed columns based on the table that the columns belong to.

  • Use the filter field to filter the columns by table or column name.

  • Use the Filters panel to filter the columns based on column attributes and generator configuration.

You can use column filters to quickly find columns that you want to verify or to update the configuration for.

Filter by table

To filter the column list to only include columns for specific tables, either:

  • Check the checkbox for each table to display columns for.

Filter by table or column name

To filter the column list by table or column name, in the filter field, begin to type text that is in the table or column name.

As you type, Structural filters the column list.

Using the Filters panel

The Filters panel provides access to column filters other than the table and column name.

To display the Filters panel, click Filters.

Searching for a filter

To search for a filter or a filter value, in the search field, start to type the value. The search looks for text in the individual settings.

For each filter, the Filters panel indicates the number of matching columns, based on the selected tables and the current filters.

Adding a filter

To add a filter, depending on the filter type, either check the checkbox or select a filter option. As you add filters, Structural applies them to the column list. Above the list, Structural displays tags for the selected filters.

Clearing the selected filters

To clear all of the currently selected filters, click Clear All.

Filters panel filters

Columns with generator recommendations

To only display detected sensitive columns for which there is a recommended generator, on the Filters panel, check Has Generator Recommendation.

At-risk columns

An at-risk column:

  • Is marked as sensitive.

  • Is included in the destination data.

  • Is assigned the Passthrough generator.

To only display at-risk columns, on the Filters panel, check At-Risk Column.

When you check At-Risk Column, Structural adds the following filters under Privacy Settings:

  • Sets the sensitivity filter to Sensitive

  • Sets the protection status filter to Not protected

  • Sets the column inclusion filter to Included

Sensitivity

You can filter the columns based on the column sensitivity.

On the Filters panel, under Privacy Settings, the sensitivity filter is by default set to All, which indicates to display both sensitive and non-sensitive columns.

  • To only display sensitive columns, click Sensitive.

  • To only display non-sensitive columns, click Not sensitive.

Note that when you check At-risk Column, Structural automatically selects Sensitive.

Protection status

You can filter the columns based on whether they have any generator other than Passthrough assigned. To filter the columns based on specific assigned generators, use the Applied Generator filter.

On the Filters panel, under Privacy Settings, the column protection filter is by default set to All, which indicates to display both protected and not protected columns.

  • To only display columns that have an assigned generator, click Protected.

  • To only display columns that do not have an assigned generator, click Not protected.

Note that when you check At-Risk Column, Structural automatically selects Not protected.

Inclusion in the destination database

You can filter the columns based on whether they are populated in the destination database. For example, if a table is truncated, then the columns in that table are not populated.

On the Filters panel, under Privacy Settings, the column inclusion filter is by default set to All, which indicates to display both included and not included columns.

  • To only display columns that are populated in the destination database, click Included.

  • To only display columns that are not populated in the destination database, click Not included.

Note that when you check At-Risk Column, Structural automatically selects Included.

Assigned generator

To only display columns that are assigned specific generators, on the Filters panel, under Applied Generator, check the checkbox for each generator to include.

The list of generators only includes generators that are assigned to the currently displayed columns and that are compatible with other applied filters.

To search for a specific generator, in the Filters search field, begin to type the generator name.

Column data type

You can filter the columns by the column data type. For example, you can only display varchar columns, or only columns that contain either numeric or integer values.

To only display columns that have specific data types, on the Filters panel, under Database Data Types, check the checkbox for each data type to include.

The list of data types only includes data types that are present in the currently displayed columns and that are compatible with other applied filters.

To search for a specific data type, in the Filters search field, begin to type the data type.

Unresolved schema changes

When the source database schema changes, you might need to update the configuration to reflect those changes. If you do not resolve the schema changes, then the data generation might fail. The data generation fails if there are unresolved conflicting changes, or if you configure Structural to always fail data generation when there are any unresolved changes.

For more information about schema changes, go to Viewing and resolving schema changes.

To only display columns that have unresolved schema changes, on the Filters panel, check Unresolved Schema Changes.

Sensitivity type

For detected sensitive columns, the sensitivity type indicates the type of data that was detected. Examples of sensitivity types include First Name, Address, and Email.

To only display columns that contain specific sensitivity types, on the Filters panel, under Sensitivity Type, check the checkbox for each sensitivity type to include.

The list of sensitivity types only includes sensitivity types that are present in the currently displayed columns.

To search for a specific sensitivity type, in the Filters search field, type the sensitivity type.

Sensitivity confidence

You can filter the columns based on the confidence level.

To only display columns that have a specific confidence level, on the Filters panel, under Sensitivity confidence, check the checkbox next to each confidence level to include.

Column nullability

You can filter the column list based on whether the column is nullable.

On the Filters panel, under Data Attributes, the nullability filter is by default set to All, which indicates to display both nullable and non-nullable columns.

  • To only display columns that are nullable, click Nullable.

  • To only display columns that are not nullable, click Non-nullable.

Column uniqueness

You can filter the column list based on whether the column must be unique.

On the Filters panel, under Data Attributes, the uniqueness filter is by default set to All, which indicates to display both unique and not unique columns.

  • To only display columns that must be unique, click Unique.

  • To only display columns that do not require uniqueness, click Not unique.

Primary or foreign keys

You can filter the column list to indicate whether to include:

  • Columns that are not primary or foreign keys.

  • Columns that are foreign keys.

  • Columns that are primary keys.

On the Filters panel, under Column Type:

  • To display columns that are neither a primary key nor a foreign key, check Non-keyed.

  • To display columns that are primary keys, check Primary key.

  • To display columns that are foreign keys, check Foreign key.

Generator overrides in a child workspace

In a child workspace, to only display columns that override the generator configuration that is in the parent workspace, on the Filters panel, check Overrides Inheritance.

Uses Structural data encryption

You can enable Structural data encryption, a configuration that allows Structural to:

  • Decrypt source data before applying the generator.

  • Encrypt generated data before writing it to the destination database.

For more information, go to Configuring and using Structural data encryption.

When Structural data encryption is enabled, the generator configuration panel includes an option to use Structural data encryption.

To only display columns that are configured to use Structural data encryption, on the Filters panel, check Uses Data Encryption.

Sorting the column list

By default, the column list is sorted first by table name, then by column name. The columns for each table display together. Within each table, the columns are in alphabetical order.

You can also sort the column list by column name first, then by table. Columns that have the same name display together. Those columns are sorted by the name of the table.

The button at the right of the Column column heading indicates the current sort order.

  • T.C indicates that the table is sorted by table, then by column

  • C.T indicates that the table is sorted by column, then by table

To switch the sort order, click the button.

Table and column name. When you click the column name, for the column table displays.

The Column column also contains the option to .

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

From the Status column, you can .

The Applied Generator column is where you .

The Applied Generator column also contains the option to .

.

When the Structural sensitivity scan , it also determines how confident it is in that determination. The Status column displays the confidence level.

Table View
display sample data for the column
select and configure the generator to assign
display and create column comments
change whether a column is sensitive
Column list on Database View
Status Values for a column
Confidence level indicators for database columns
Unprotected column that has a recommended generator
Disable generator dropdown for a foreign key column
Column with a generator configuration that overrides the parent workspace
Filtering columns by name
Filters panel for columns
Using the column filter search
Filters panel with filters selected
Sort button in the Column heading
Apply a filter to the table list
How Structural identifies sensitive values
identifies a value as belonging to a sensitivity type