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Attribute Synchronization

Configure how user attributes from a source of identity are synchronized for target user accounts

Attribute synchronization ensures that identity attributes in target systems remain up to date with the corresponding attributes in the source of truth. Veza Lifecycle Management provides configuration at two levels to control how and when attributes are synchronized.

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Action Level

At the action level, there are two distinct options to govern provisioning and user update processes:

  • Create new users - When enabled, the action will create new user accounts that don't exist in the target system

  • Update active users - When enabled, the action can update existing user accounts with attribute changes from the source of truth

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Attribute Level

At the attribute level, there are two explicit choices that define how and when attribute values are applied to user accounts:

  • Set for new users only - The attribute value is set only when creating new user accounts

  • Set for new and existing users - The attribute value is set for new accounts and updated for existing accounts when changes are detected

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You may not want to enable "Set for new and existing users" for attributes like user principal name, which may change due to marital status or legal name corrections but shouldn't be automatically updated in all systems.

Both levels must be properly configured for an attribute to be continuously synchronized. For example, to keep an employee's department updated:

  1. Enable Update active users on the Sync Identity action

  2. Select Set for new and existing users for the department attribute

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Recommended Settings

Set for new and existing users (continuously sync attributes that change during employment):

  • First Name, Surname

  • Department

  • Title

  • Manager

Set for new users only (preserve stable identifiers):

  • Active Directory sAMAccountName

  • Email Addresses (for Email Write-Back action)

This configuration ensures that dynamic attributes remain up to date while preserving stable identifiers.

Cost Center

  • AD Distinguished Name (DN)

  • AD User Principal Name (UPN)

  • AD Email

  • System Attributes

    Computed properties for advanced workflow triggering and conditional transformations in Lifecycle Management

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    Overview

    System attributes are computed properties that Lifecycle Management automatically generates during identity processing. These attributes enable advanced automation scenarios by providing runtime information about identity changes and transformation results.

    All system attributes follow the sys_attr__ prefix convention and cannot be manually set or modified.

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    Available System Attributes

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    sys_attr__is_mover

    A persistent boolean attribute that indicates whether an identity has undergone changes to monitored properties.

    Type: Boolean Persistence: Stored with identity record Available in: Workflow triggers, conditions, and transformers

    Configuration: Define monitored properties in the policy configuration:

    Workflow Trigger Example:

    Combined Condition Example:

    The attribute is automatically set to true when any property in mover_properties changes during identity update. It is cleared when the identity is unchanged in an extraction cycle, and excluded from change detection to prevent recursive updates.

    System attribute names are case-sensitive and must be lowercase in all expressions.

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    sys_attr__would_be_value

    A transient attribute that provides a preview of the transformation result during conditional evaluation.

    Type: String Persistence: Transient (exists only during IF statement evaluation) Available in: Conditional transformers only

    Usage Example - Conditional Domain Addition:

    The above transformer will check if the transformed email already contains "@", preserve existing email addresses, and add domain only when needed.

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    sys_attr__would_be_value_len

    A transient attribute that provides the character length of the transformation result during conditional evaluation.

    Type: Number Persistence: Transient (exists only during IF statement evaluation) Available in: Conditional transformers only

    Usage Example - Progressive Username Truncation:

    For "Leonevenkataramanathan Foster":

    • First check (≤30 chars): leonevenkataramanathan.foster (30 chars - passes first condition)

    • If >30 chars, second check (≤20 chars): leonevenkataramana.foster (25 chars - fails second condition)

    • If >20 chars, fallback: l.f (3 chars - always succeeds)

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    Integration with NEXT_NUMBER

    Preview attributes work with the NEXT_NUMBER transformer for generating unique alternatives:

    This evaluates the base value length before applying numbering, ensuring the final result (including numbers) meets constraints.

    Only one NEXT_NUMBER transformer is allowed per conditional branch.

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    Workflow Trigger Properties

    The sys_attr__is_mover attribute supports additional trigger properties for fine-grained control:

    This workflow triggers only when:

    • The identity is marked as a mover (department or location changed)

    • The identity is active

    • At least one of the trigger_properties has changed since last extraction

    Performance Notes

    • Mover Detection: Comparison occurs for all properties in mover_properties during each extraction

    • Preview Evaluation: Each IF branch with preview attributes requires transformation execution

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    See Also

    • - Complete SCIM filter syntax for workflow conditions

    • - Complete list of transformation functions

    • - Attribute transformation concepts and examples

  • Alternatives with NEXT_NUMBER: l.f2, l.f3, l.f4

  • Optimization: Place most common conditions first to minimize preview evaluations
  • Caching: Preview values are calculated once per condition branch and reused

  • Policies - Configuring mover properties and workflows
    Trigger Conditions Reference
    Transformer Functions Reference
    Transformers
    {
      "mover_properties": ["department", "manager_id", "title", "location"]
    }
    sys_attr__is_mover eq true
    sys_attr__is_mover eq true and department eq "Engineering" and is_active eq true
    IF sys_attr__would_be_value co "@"
      {email | LOWER}
    ELSE
      {email | LOWER}@company.com
    IF sys_attr__would_be_value_len le 30
      {first_name | LOWER}.{last_name | LOWER | NEXT_NUMBER, 2, 3}
    ELSE IF sys_attr__would_be_value_len le 20
      {first_name | LOWER | FIRST_N, 10}.{last_name | LOWER | NEXT_NUMBER, 2, 3}
    ELSE
      {first_name | LOWER | FIRST_N, 1}.{last_name | LOWER | FIRST_N, 1 | NEXT_NUMBER, 2, 3}
    IF sys_attr__would_be_value_len le 15
      {username | NEXT_NUMBER, 2, 5}
    ELSE IF sys_attr__would_be_value_len le 15
      {username | FIRST_N, 13 | NEXT_NUMBER, 2, 5}
    {
      "trigger_properties": ["department", "location"],
      "trigger_string": "sys_attr__is_mover eq true and is_active eq true"
    }

    Lookup Tables

    Use lookup tables to transform identity attributes for target systems

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    Overview

    You can use Lookup transformers to convert identity attributes from a source system into appropriate values for target systems based on CSV reference tables. This is particularly useful when mapping values between systems that use different naming conventions, codes, or formats for the same conceptual data.

    For example, you might need to transform a "Location" attribute from Workday (which might be stored as location codes like "MN001") into corresponding values for country, country code, or city names in a target system.

    Use Table Lookup Transformers when:

    • You need to map source attribute values to different values in target systems

    • You have standardized reference data that must be consistent across applications

    • You need to extract different pieces of information from a single attribute value

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    Examples

    1. Geographic Information:

      • Transform location codes to country, region, city, or timezone information

      • Map office codes to physical addresses or facility types

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    How It Works

    The Table Lookup Transformer references CSV-based mappings between source and destination values. When synchronizing user attributes, Veza:

    1. Takes the source attribute value

    2. Looks up this value in the specified lookup table

    3. Returns the corresponding value from the designated return column

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    Lookup Table Structure

    Lookup tables are CSV files with columns that map values from a source of identity to destination values. Each row represents a mapping entry. The first row must contain the column headers.

    For example, a location mapping table might look like:

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    Creating and Managing Lookup Tables

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    Creating a Lookup Table

    To create a new lookup table:

    1. Navigate to the Lookup Tables tab within your policy configuration

    2. Click Edit mode to enable policy changes

    3. Click Add New to create a new lookup table

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    Managing Lookup Tables

    From the Lookup Tables tab, you can:

    • Edit table descriptions or upload a new CSV

    • Delete tables that are no longer needed

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    Using Table Lookup Transformers

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    Basic Syntax

    To use a Table Lookup Transformer in a common or action-synced attribute:

    1. In Destination Attribute, choose the attribute on the target entity that will be updated

    2. In Formatter, choose the source attribute to transform

    3. In Pipeline Functions, specify the lookup table name, the column to match against, and the column containing values to return.

    The full syntax for using lookup table transformers is:

    Where:

    • <value> is the source attribute to transform (e.g., {location})

    • <table_name> is the name of the lookup table to use

    • <column_name>

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    Examples

    Assuming a user has "location": "IL001" and a lookup table named locationTable structured as shown earlier:

    Formatter
    Result

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    Advanced Features

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    Pipeline Transformations

    You can combine lookup transformations with other transformation functions in a pipeline:

    This would look up the state_code corresponding to the location value and convert it to lowercase.

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    Handling Missing Values

    When a lookup value is not found in the table, the transformation will fail for that specific attribute.

    For full coverage, ensure your lookup table includes entries for all possible source values that may be encountered during provisioning.

    To ensure robust provisioning workflows, it's important to include all expected values in your lookup table, validate source data before implementing lookup transformations, and test transformations with representative data sets.

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    Technical Details

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    Implementation Notes

    • Lookup tables are immutable and automatically deleted when no longer referenced by any policy version

    • Multiple policy versions can reference the same lookup table (e.g., an active version and a draft version)

    • Lookup tables are defined at the policy level and can be referenced by any transformer within the policy

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    Best Practices

    1. Standardize Naming: To use a lookup-based transformer, you will reference the table by file name. Apply consistent conventions for both the table and columns.

    2. Document Mappings: Add descriptions for each lookup table to explain its purpose

    3. Validate Data: Ensure lookup tables are complete and accurate before using them in transformers. Consider how lookup tables will be maintained over time, especially for values expected to change.

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    Troubleshooting

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    Common Issues

    Issue
    Resolution

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    Related Topics

    You have complex mapping requirements that built-in transformers cannot support
    Organizational Mapping:
    • Convert department codes to department names or business units

    • Map cost centers to budget codes or accounting categories

  • System-Specific Configurations:

    • Transform job titles to role designations in target systems

    • Convert skill codes to certification requirements or training needs

  • Applies this value to the target attribute
    Provide a Name and optional Description for the lookup table
  • Drag a CSV file or click Browse to upload your reference data

  • Review the automatically detected column names

  • Click Save to store the lookup table

  • is the column in the table to match against
  • <return_column_name> is the column containing the value to return

  • Lookup tables can have multiple columns to support different transformations from the same reference data
    Lifecycle Management Workflows

    {location} | LOOKUP locationTable, location_code, city

    "Chicago"

    {location} | LOOKUP locationTable, location_code, state

    "Illinois"

    {location} | LOOKUP locationTable, location_code, state_code

    "IL"

    Value not found in lookup table

    Add the missing mapping to the lookup table with the correct source value

    Incorrect column name referenced

    Check the column names in your lookup table (they are case-sensitive)

    Unexpected transformation results

    Verify the lookup table content and ensure the correct columns are specified

    Attribute Transformers
    Common Transformers
    Pipeline Functions
    Configuring an action-level attribute transformer using lookup tables.
    location_code,state_code,state,city
    MN001,MN,Minnesota,Minneapolis
    CA001,CA,California,Los Angeles
    TX001,TX,Texas,Houston
    TX002,TX,Texas,Austin
    {<value> | LOOKUP <table_name>, <column_name>, <return_column_name>}
    {location | LOOKUP locationTable, location_code, state_code | LOWER}

    Attribute Mapping

    How source system properties become Veza attributes

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    Overview

    When connecting to integrated systems (see Veza Integrations), Veza ingests properties from the source systems (e.g., Workday, Okta, Active Directory) and normalizes them into standardized attributes that appear when configuring Workflow trigger conditions, configuring Actions, and in Identities views.

    While these standardized attributes are intended to ensure consistent naming across different systems, it is important to understand that some attributes may appear differently than their original names in the source system.

    You can retrieve the original attribute names for enabled Lifecycle Management integrations using the API.

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    Attribute Naming Conventions

    Veza normalizes all property names for consistency:

    Original Format
    Veza Format
    Rule Applied

    The following normalization rules typically apply:

    • Source properties are converted to lowercase

    • Any spaces and hyphens become underscores

    • Special characters removed

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    Attribute Types and Mappings

    The following sections include some examples of how Veza handles attributes from common integrations.

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    Standard Attributes

    Veza recognizes and standardizes many common attributes across source systems:

    Attribute
    Type
    Description
    Example Value

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    Source-Specific Mappings

    Veza will make conversions to some attribute names from the source integration. For example, sAMAccountName in Microsoft Active Directory is shown as account_name for Active Directory Users in Veza Access Graph.

    Workday → Veza

    Workday Property
    Veza Attribute
    Notes

    Okta → Veza

    Okta Property
    Veza Attribute
    Notes

    Active Directory → Veza

    AD Property
    Veza Attribute
    Notes

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    Custom Properties

    Some integrations support custom property extraction for organization-specific fields from custom reports or extended schemas:

    • Always prefixed with customprop_

    • Automatically discovered during extraction once enabled

    • Follow standard normalization rules (lowercase, underscores)

    Examples:

    • customprop_department_code - Custom department identifier

    • customprop_employeeou - Organizational unit

    • customprop_region - Geographic region

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    System Attributes

    Some entity attributes are computed by Veza, and not derived from source data:

    • sys_attr__is_mover - Identity has changed monitored properties

    • sys_attr__would_be_value - Preview value in conditional transformers

    • sys_attr__would_be_value_len - Preview value length in conditional transformers

    See for details.

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    Using Attributes in Workflows

    When configuring a Workflow trigger condition or an action that syncs attributes, you can choose from available attributes using a dropdown menu.

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    Primary vs Secondary Sources

    Primary Source - Attributes from the main identity source appear without prefixes:

    Secondary Sources - Attributes from additional sources are prefixed with the entity type:

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    Example Usage

    Lifecycle Management uses two different expression syntaxes depending on the context:

    In Workflow Conditions (SCIM Filter Syntax):

    Trigger conditions use SCIM filter syntax to evaluate boolean expressions. See for complete documentation.

    In Transformers (Formatter/Pipeline Syntax):

    Attribute transformers use curly braces and pipes to produce output values. See for complete documentation.

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    Important: These syntaxes cannot be interchanged. Use SCIM filter syntax only in condition fields, and formatter syntax only in attribute mapping fields.

    With Secondary Sources (in Conditions):

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    See Also

    • - Computed attributes for advanced scenarios

    • - Modifying and combining attribute values

    • - Using attributes in workflow conditions

    CamelCase converted to snake_case
  • Custom fields are identified with a customprop_ prefix

  • System-computed fields are identified with the sys_attr__ prefix

  • title

    string

    Job title

    Senior Engineer

    business_title

    string

    Business position

    Senior Engineer

    manager

    string

    Manager reference

    managers

    list

    List of managers

    [John Smith]

    is_active

    boolean

    Active status

    true

    hire_date

    date

    Employment start date

    2024-01-15

    cost_center

    string

    Financial allocation

    CC-1000

    Employee Type

    employee_types

    List (e.g., Full Time)

    Manager

    managers

    List of manager names

    manager

    manager

    Manager's email/ID

    department

    department

    Department name

    title

    title

    Job title

    customprop_project_code - Project allocation

    Employee ID

    employee_id

    Spaces → underscores

    BusinessTitle

    business_title

    CamelCase → snake_case

    Cost-Center

    cost_center

    Special chars removed

    Department Code

    customprop_department_code

    employee_id

    string

    Employee identifier

    E-98765

    email

    string

    Primary email

    [email protected]envelope

    department

    string

    Department name

    Worker ID

    workday_id

    Unique worker identifier

    Employee ID

    employee_id

    Employee number

    Business Title

    business_title

    Job position

    Cost Center

    cost_center

    login

    login

    Username

    email

    email

    Primary email

    status

    status

    ACTIVE, SUSPENDED, etc.

    department

    department

    sAMAccountName

    account_name

    Pre-Windows 2000 login

    distinguishedName

    distinguished_name

    Full LDAP path

    userPrincipalName

    user_principal_name

    user@domain format

    memberOf

    member_of

    ListLifecycleManagerDatasources
    System Attributes
    Trigger Conditions Reference
    Transformers
    System Attributes
    Transformers
    Policies
    Selecting attributes in a workflow trigger condition.

    Custom fields prefixed

    Engineering

    Financial allocation

    Department name

    List of group DNs

    workday_id
    employee_id
    business_title
    hire_date
    email
    customprop_department_code
    OktaUser.login
    OktaUser.department
    AzureADUser.job_title
    ActiveDirectoryUser.distinguished_name
    employee_types co "Full Time" and department eq "Engineering"
    {first_name}.{last_name}@{customprop_domain}.com
    OktaUser.status eq "ACTIVE" and WorkdayWorker.is_active eq true
    [email protected]envelope

    Attribute Transformers

    Configure how user attributes from a source of identity are transformed for target user accounts

    When creating workflows in Lifecycle Management policies to create, sync, or deprovision identities, you will use attribute transformers to specify how user attributes for target accounts should be structured.

    The target attributes to create or update are typically mapped and, optionally, transformed from user metadata in the source of identity, such as an identity provider, HR system, or CSV upload. Attributes can be synchronized once or kept continuously in sync as changes occur throughout the user's employment lifecycle.

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    Attribute transformers are also available when mapping columns in CSV Upload integrationsarrow-up-right. This enables you to combine columns, reformat dates, standardize case, and apply other transformations during CSV import—without requiring Lifecycle Management workflows.

    For example, attribute mapping and transformation can be used across Joiner, Mover, and Leaver scenarios:

    • Joiner: Set new Azure AD User Principal Name to {source username}@your-email-domain.com. This is an example of mapping multiple attributes and performing a transformation. More specifically, you use the attribute transformer to generate an email address for new joiners. Use the source username (user_principal_name) from the source of identity (Azure AD UPN) for the first part (user attribute), while your-email-domain.com is used for the last part (target attribute).

    • Mover: Always update a user’s “Manager” and “Department” attributes in Okta to match the user’s manager and department in Workday, a source of identity, whenever a department change or other employee mobility event occurs. This is an example of attribute mapping with continuous synchronization.

    When synchronizing a user’s attributes, Veza may apply many transformations to convert the source attribute values into a more suitable format intended for the target application as a user account attribute.

    For example, a transformer might remove the domain from an email address, replace special characters, or convert a string with uppercase letters to lowercase letters.

    See for detailed information.

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    Key Terminology

    Term
    Description
    Examples

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    Adding transformers

    Common transformers define one or more rules to apply when synchronizing the attributes of a target identity. Use them at the Policy level where you want to create or update attributes using the same conventions across multiple sync or deprovision actions. When you need to configure a one-time individual action in a workflow, such as a specific attribute, then you use the transformer at the Action level.

    At the Policy level, you configure a transformer with basic details, including how to source the value of each attribute:

    1. Assign a name and description to the transformer, and specify the data source to which it applies.

    2. Entity Type: Choose the target entity type in the destination system.

    3. Click Add Attribute. The Destination Attribute dropdown will list available attributes for the chosen entity type.

    After creating a common transformer, you can select it when editing a workflow action. You can edit or delete common transformers on the Edit Policy > Common Transformers tab. Remember that “Sync Identity” and “De-Provision Identity” actions can have action-level transformers override common transformers. If the same destination attribute is defined in both, the action-level transformer will take precedence.

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    Formatters

    Formatters specify the actual value of the attribute to synchronize. The target attribute can be set to a specific value, synchronized with a source attribute, transformed using a function, or a combination of these.

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    Some formatters should enable continuous synchronization for the attribute, while others should not. For example, the value of "Created By" should be immutable once a user account is provisioned. Other attributes that represent a state or status should be synchronized throughout the user's or account's lifecycle.

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    Simple Value Setting

    To create a destination attribute with a fixed value, enter the desired value when configuring the formatter. For setting the creator attribute:

    Destination Attribute
    Formatter
    Continuous Sync

    For activating a re-hired employee:

    Destination Attribute
    Formatter
    Continuous Sync

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    Empty Values

    To set empty values (common for de-provisioning flows):

    Destination Attribute
    Formatter
    Continuous Sync

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    Source of Identity Formatters

    Target attributes can be updated based on attributes belonging to the source of identity. To reference the value of a source entity attribute, use the format {<source_attribute_name>}.

    Examples:

    Destination Attribute
    Formatter Example
    Continuous Sync

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    Alias Definitions

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    Early Access: Alias Definitions is currently in early access. Contact your Veza representative to enable this feature for your tenant.

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    When to use aliases

    By default, when you reference an attribute such as {department} in a formatter, the system searches through your configured identity sources in order (primary first, then secondary sources). This works well for simple policies with a single source of identity.

    Aliases become useful when:

    • Multiple integrations share the same entity type (e.g., two Active Directory instances, or when your source of identity and sync target use the same entity type)

    • A policy involves multiple integrations that have attributes with the same name

    • You need to explicitly control which system's attribute value is used

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    Alias Naming: The system automatically adds a $ prefix to all alias names. For example, if you create an alias named workday in the UI, it becomes $workday when used in formatters and conditions.

    Example: HR System to Directory Sync

    A policy syncs identities from an HR system (Workday) to a directory (Active Directory). Both have a department attribute. Without aliases, {department} resolves from whichever system appears first in the search order. With configured aliases hr and directory (which become $hr and $directory), you can explicitly reference {$hr.department} to ensure you're using the authoritative HR value.

    Aliases can be used in:

    • Attribute formatters

    • Workflow trigger conditions

    • Action conditions

    • Mover property definitions

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    Configuring aliases

    Aliases provide shorthand references to specific integrations and entity types, making transformers and conditions more readable in complex policies.

    To configure aliases, open a Lifecycle Management policy, click Edit, and navigate to the Alias Definitions tab. Each alias requires:

    • Alias Name: Must start with $ followed by at least one lowercase letter, number, or underscore. Additional $ characters can appear after the first character. The $ prefix is added automatically if omitted. Valid examples: $workday, $hr_system, $ad$corp. Invalid examples: $, $AD (uppercase), $$double (multiple leading $

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    Validation Rules: Alias names allow only lowercase alphanumeric characters, underscores, and $. They must start with exactly one $ (not zero, not multiple), and cannot be $target (reserved for action-level attribute references).

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    Testing and Validation: Aliases work in test formatters, allowing you to validate your formatter expressions before deployment. Additionally, alias-resolved attribute values appear in dry run results, so you can preview exactly which values will be synced.

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    Input and output resolution

    Aliases can resolve attributes from two contexts:

    • Input: Values from the source system before any sync action runs (the authoritative data)

    • Output: Values currently in the target system (what's already provisioned)

    By default, the system checks output first, then falls back to input. Use suffixes to explicitly control resolution:

    Suffix
    Resolves From
    Example
    Use Case
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    When to Use Suffixes: Use $in when you need the authoritative value from the source system (e.g., HR system). Use $out when you need to compare against what's currently provisioned in the target. Without a suffix, the system checks the target first—useful when you want the most recent value regardless of source.

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    Comparison operators

    Use these operators in IF conditions to compare attribute values:

    Operator
    Meaning
    Supported Types

    Combine conditions with and, or, or negate with not.

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    String List Attributes: For multi-value attributes (string lists), only the co (contains) operator is supported. Use it to check if the list includes a specific value, for example: IF $workday.roles co "Manager".

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    Examples

    In attribute formatters:

    In LCM Workflow Conditions (comparing source and target values):

    Multiple integrations with the same entity type:

    For organizations with multiple Active Directory domains (e.g., corporate employees and contractors), you can create distinct aliases to control which AD integration is used:

    • Configure alias corp_ad → Integration: AD_Corporate, Entity Type: ActiveDirectoryUser

    • Configure alias contractor_ad → Integration: AD_Contractors, Entity Type: ActiveDirectoryUser

    Then explicitly reference the correct domain in your formatters:

    This ensures you're using the department attribute from the corporate AD integration rather than the contractor AD integration, even though both use the same ActiveDirectoryUser entity type.

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    Transformation functions

    Based on the user metadata available from your source of identity (SOI), you may need to convert a full email address to a valid username, standardize a date, or generate a unique identifier for users provisioned by Veza. Suppose an attribute value needs to be altered to be compatible with the target system. In that case, you can transform the value of a source attribute or apply a range of other functions to generate the target value.

    Formatter expressions use the following syntax: {<source_attribute_name> | <FUNCTION_NAME>,<param1>,<param2>}

    For example:

    Destination Attribute
    Formatter
    Description
    Example

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    Transformation function categories

    Refer to the page for complete documentation of all supported functions, parameters, and usage examples. The reference includes:

    Category
    Functions
    Use Cases
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    Contact Veza if you require additional transformations for your use case.

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    Pipeline Functions {#pipeline-functions}

    You can pipeline multiple transformation functions together, separated by a vertical bar (|). Each will apply in sequence, allowing for complex attribute formatters that use the output of one function as the input of another.

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    Example Pipeline Functions

    • {name | UPPER}

      • If name = Smith, the result is SMITH.

    • {first_name | SUB_STRING,0,1 | LOWER}.{last_name | LOWER}

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    Testing Transformers Inline

    Before deploying transformers in production policies, you can validate formatter expressions directly in the Veza UI. This allows you to verify that your transformation logic produces the expected output without affecting live data.

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    Using the Test Interface

    When adding or editing a transformer in a policy, look for the Test Formatter button next to the transformer field. Clicking it opens a test dialog:

    1. Enter your transformer expression in the Attribute Transformer field

    2. Click the Test Formatter button to open the test dialog

    3. The dialog shows input fields for each attribute referenced in your expression (e.g., {first_name}, {email})

    The test dialog is available wherever transformers are configured, including:

    • Action synced attributes

    • Unique identifiers

    • Common transformers

    • Date formatters

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    Testing Examples

    Expression
    Test Input
    Expected Output

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    Testing Pipeline Functions

    For complex pipelines, test incrementally:

    1. Test the first function alone to verify it handles the input correctly

    2. Add each subsequent pipe and verify intermediate results

    3. Validate the complete pipeline produces the final expected value

    This step-by-step approach helps isolate issues when a transformation doesn't produce the expected output.

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    The test interface uses sample data you provide. Ensure your test values accurately represent the source attribute data types and formats you'll encounter in production.

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    When to Use Inline Testing vs. Dry Run

    Scenario
    Use

    Use inline testing during transformer development, then validate the complete policy with a dry run before deploying to production.

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    Common Transformers

    As part of implementing Lifecycle Management (LCM) processes with Veza, you should create sets of common transformers to define how values such as username, login, or ID are sourced for each LCM Policy. These transformers can then be reused across all identity sync and deprovision policy workflows.

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    Create common transformers to consistently form attributes for specific entity types, and reuse them to avoid errors and save time when creating actions for that entity type. The order of common transformers matters when multiple transformers set the same destination attribute. Drag-and-drop to reorder common transformers and control precedence.

    For example, defining a common synced attribute to describe how to format Azure AD account names {username}@evergreentrucks.com enables reuse across multiple workflow actions. You can also define synced attributes at the action level when they are used only once within a policy, such as setting the primary group DN and OU of de-provisioned identities to a group reserved for terminated accounts.

    Common Transformer Examples:

    Transformer & Entity Type
    Attribute
    Value Format
    Continuous Sync
    Description

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    $target Attribute Transformer Function

    The $target attribute transformer function is used when a value consists of one or more attributes that require an operation(s), making it too complex to transform, but it needs to be reused.

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    Important: The $target function can only be used within the same Action.

    For example, an email address consists of [email protected]. However, you must use the format . By using the $target function, you reuse only one attribute, username, while not changing the other two attributes (firstname_lastname).

    Example:

    Destination Attribute

    Formatter

    Formatter

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    Custom Attribute Transformer Function

    The Custom Attribute Transformer function allows you to define a custom transformer that acts as an alias for applying one or more transformer functions.

    For example, you can define a custom function named $CLEAN, which is used as {first_name | $CLEAN}. This function can consist of a series of transformer functions such as | ASCII | LOWER | REMOVE_CHAR |.

    To define a custom attribute transformer, use the following guidelines:

    Policy Version Definitions

    • Custom functions must be defined as part of the policy version.

    • These definitions are structured similarly to hard-coded definitions and are returned in the same format, allowing the Veza UI to handle them without modification.

    • The API for updating and retrieving a policy version must also support these custom function definitions.

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    Naming Convention: Custom functions must be in ALL CAPS and prefixed with a $ to avoid conflicts with built-in functions.

    Custom Attribute Transformer Limitations

    The following custom definitions are not supported:

    • Transformer functions with included transformer parameters

    • Nested transformer functions

    • Transformer functions with parameters

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    Appending Multi-Value Attribute (Active Directory only)

    As part of the Identity Sync action, you can append values to multi-value Active Directory attributes without replacing existing values. This ensures that existing attribute values are preserved when adding new ones.

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    This feature is specific to Active Directory and is not available for other integrations.

    Supported Multi-Value Attributes:

    Active Directory supports appending for the following multi-value attributes:

    • organizationalStatus, departmentNumber, employeeType

    • servicePrincipalName, proxyAddresses

    Syntax:

    Use the >> prefix before the array to append values:

    Appending syntax supports two array formats:

    • With quotes (JSON format): >>[``"Active", "Permanent"]

    • Without quotes (simple format): >>[Active, Permanent]

    When you use this syntax:

    1. New values are added to the end of the existing attribute values

    2. Duplicate values are automatically removed

    3. The order of existing values is preserved

    For example, ff an Active Directory user has:

    And you apply the transformer:

    The resulting value is:

    Note that "Employee" was already present and not duplicated.

    Setting vs. Appending:

    • To Replace existing values: Use [value1, value2] (without >>)

    • To Append to existing values: Use >>[value1, value2] (with >>)

    Additional Notes:

    • The append prefix (>>) only works for multi-value attributes. It is ignored for single-value attributes

    • If the attribute has no existing values, the values are simply set (no difference from non-append behavior)

    • Both the appending syntax and the standard array syntax support arrays with or without quotes around values

    Leaver: Move a user’s Active Directory account to an Organizational Unit (OU) reserved for terminated accounts.

    Destination Attribute: Choose the attribute that Veza will create or update for the target entity.

  • Formatter: Choose how the destination attribute should be formatted. Specify the value, a {source_attribute}, or apply Transformation Functions.

  • Pipeline Functions: Combines a series of attribute formatters with the pipe ( | ) character that runs the value of an attribute in sequential order, where the output of one formatter becomes the input of the following formatter, thus the name, pipeline.

  • See Pipeline Functions for more examples.

    • Continuous Sync: Enabling this option ensures that the attribute is always synced, while applying any defined transformations. By default, attributes will not be synced if the target identity already exists.

    You want to compare values between source and target systems while defining LCM Workflow Conditions

  • You need to detect movers based on changes in a specific system

  • Test formatters (for validation before deployment)

  • ).
  • Integration: The data source containing the entity type.

  • Entity Type: The entity type to reference (e.g., WorkdayWorker, OktaUser).

  • ew

    Ends with

    String

    lt

    Less than

    Number, timestamp

    le

    Less than or equals

    Number, timestamp

    gt

    Greater than

    Number, timestamp

    ge

    Greater than or equals

    Number, timestamp

    Date/time

    DATE_FORMAT, DATE_ADJUST, DATE_ADJUST_DAY, ASSUME_TIME_ZONE, UTC_TO_TIME_ZONE, NOW

    Convert and manipulate dates

    Character encoding

    ASCII, REMOVE_DIACRITICS

    Handle international characters

    Lookup

    LOOKUP, FROM_ENTITY_ATTRIBUTE, FROM_MANY_ENTITIES_ATTRIBUTE

    Cross-reference data from tables or entities

    Generation

    NEXT_NUMBER, UUID_GENERATOR, RANDOM_INTEGER, RANDOM_STRING_GENERATOR, RANDOM_ALPHANUMERIC_GENERATOR, RANDOM_NUMBER_GENERATOR

    Create unique values

    Domain

    REMOVE_DOMAIN

    Extract usernames from email addresses

    Formatting

    COUNTRY_CODE_ISO3166, LANGUAGE_RFC5646, PHONE_NUMBER_E164

    Standardize to international formats

    If first_name = John and last_name = Smith, the result is j.smith.

  • {email | REMOVE_DOMAIN}

    • If email = [email protected], the result is john.smith.

  • {email | REPLACE_ALL, " ", "."}

    • If email = john [email protected], the result is [email protected].

  • {location | LOOKUP locationTable, location_code, city}

    • If location = IL001, the result is Chicago (using a lookup table named locationTable).

  • {start_date | DATE_FORMAT, "01/02/2006" | UPPER}

    • If start_date = 2023-03-15, the result is 03/15/2023 (DATE_FORMAT doesn't typically need UPPER, but shows pipeline capability).

  • {hire_date | DATE_FORMAT, "Jan 2, 2006" | REPLACE_ALL, " ", "_"}

    • If hire_date = 2023-03-15, the result is Mar_15,_2023.

  • {office_code | TRIM_CHARS_LEFT, ".0" | TRIM_CHARS_RIGHT, ".USCA"}

    • If office_code = 000.8675309.USCA, the result is 8675309.

  • {username | REMOVE_CHARS, ".-_" | TRIM | UPPER}

    • If username = "–john.doe_–", the result is JOHNDOE.

  • {employee_id | REMOVE_CHARS, "#" | TRIM_CHARS, "0" | LEFT_PAD, 6, "0"}

    • If employee_id = "##001234##", the result is 001234.

  • {department | REMOVE_WHITESPACE | LOWER | REPLACE_ALL, "&", "and"}

    • If department = "Sales & Marketing", the result is salesandmarketing.

  • TEST{| RANDOM_INTEGER, 1000, 9999}

    • Generates test IDs like TEST4827, TEST8391 (see RANDOM_INTEGER for details).

  • Enter sample values for each attribute

  • Click Test Formatter in the dialog to evaluate the expression

  • View the result to verify the transformation produces expected output

  • Click Save to close the dialog, or Cancel to discard changes

  • user_principal_name

    `{first_name

    SUB_STRING,0,1

    LOWER}.{last_name

    email

    {first_name}{last_name}@company.com

    Yes

    Email address

    OktaAccountTransformer OktaUser

    login

    `{first_name

    SUB_STRING,0,1

    LOWER}.{last_name

    email

    {first_name}{last_name}@company.com

    Yes

    Email address

    username_prefix

    `{first_name

    SUB_STRING,0,1

    LOWER}.{last_name

    AzureADTransformer AzureADUser

    principal_name

    {first_name}{last_name}

    No

    Primary identifier

    mail_nickname

    `{first_name

    SUB_STRING,0,1

    LOWER}{last_name

    display_name

    {first_name} {last_name}

    Yes

    Display name

    GoogleAccountTransformer GoogleWorkspaceUser

    email

    {first_name}{last_name}@company.com

    No

    Primary email

    email_addresses

    {username}@company.com

    No

    Email list

    recovery_email

    {personal_email}

    Yes

    Backup email

    ContractorTransformer ActiveDirectoryUser

    account_name

    c-{username}

    No

    Contractor prefix

    distinguished_name

    CN={first_name} {last_name},OU=Contractors,OU={department},DC=company,DC=local

    Yes

    Contractor OU

    description

    Contractor - {vendor_company} - Start Date: {start_date}

    Yes

    Metadata

    RegionalEmailTransformer ExchangeUser

    email_address

    {username}@{region}.company.com

    No

    Regional email

    alias

    {first_name}.{last_name}@{region}.company.com

    Yes

    Regional alias

    member, memberOf, roleOccupant
  • url, wWWHomePage

  • otherTelephone, otherMobile, otherIpPhone, otherFacsimileTelephoneNumber, otherHomePhone, otherPager, otherMailbox

  • And additional multi-value attributes including: objectClass, postalAddress, postOfficeBox, seeAlso, userCertificate, userSMIMECertificate, userPKCS12, securityIdentifierHistory, altSecurityIdentities, businessCategory, carLicense, homePostalAddress

  • New values appear after existing values in the order specified

    Source of Identity (SOI)

    The system holding authoritative user data—the "source of truth"

    HR systems (Workday, BambooHR), identity providers (Azure AD, Okta), CSV uploads

    Target Application

    The system where user accounts are created or updated using SOI data

    Active Directory, Okta, Google Workspace, SaaS applications

    created_by

    “Veza”

    Disabled

    isActive

    true

    Enabled

    manager_id

    " "

    Enabled

    isActive

    false

    Enabled

    first_name

    {first_name}

    Enabled

    last_name

    {last_name}

    Enabled

    email

    {first_name}.{last_name}@domain.com {first_name}_{last_name}@domain.com {last_name}@domain.com {firstname_initial}{last_name}@domain.com {firstname_initial}-{last_name}@domain.com {firstname_initial}{middlename_initial}{last_name}@domain.com {last_name}-{firstname_initial}@domain.com

    -

    (none)

    Output, then input

    {$workday.department}

    General attribute access

    $in

    Source only

    {$workday$in.department}

    Get the authoritative source value

    $out

    Target only

    {$workday$out.department}

    eq

    Equals

    Boolean, string, number, timestamp

    ne

    Not equals

    Boolean, string, number, timestamp

    co

    Contains

    String, string list

    sw

    Starts with

    username

    `{email | REMOVE_DOMAIN}`

    Removes the domain from the email to create username

    "jsmith" is the output derived from [email protected]

    user_id

    `f{id | UPPER}`

    Converts ID to uppercase

    JSMITH" is the output derived from the userid, "jsmith"

    String case

    UPPER, LOWER, TITLE_CASE, SENTENCE_CASE, LOWER_CAMEL_CASE, UPPER_CAMEL_CASE, LOWER_SNAKE_CASE, UPPER_SNAKE_CASE

    Standardize naming conventions

    String manipulation

    TRIM, TRIM_CHARS, REMOVE_CHARS, REMOVE_WHITESPACE, REPLACE_ALL, APPEND, PREPEND

    Clean and format string data

    Substring

    FIRST_N, LAST_N, SUB_STRING, SPLIT

    Extract portions of values

    Padding

    LEFT_PAD, RIGHT_PAD, ZERO_PAD

    Create fixed-width identifiers

    UPPER

    john.doe

    JOHN.DOE

    {email | SPLIT("@") | INDEX(0)}

    [email protected]

    john.doe

    {start_date | DATE_FORMAT("2006-01-02")}

    2025-01-15T10:30:00Z

    2025-01-15

    {name | LOWER | REPLACE_ALL(" ", ".")}

    John Smith

    Validating a single transformer expression

    Inline Testing

    Testing how transformers work with real entity data

    Dry Run

    Verifying complete policy workflow execution

    Dry Run

    ADAccountTransformer ActiveDirectoryUser

    account_name

    {display_full_name}

    No

    Basic account name

    distinguished_name

    CN={first_name} {last_name},OU={department},OU={location},DC=company,DC=local

    Yes

    Full AD path

    Attribute Synchronization
    Transformer Reference
    [email protected]envelope

    Get the current target value

    String

    john.smith

    {$workday.first_name | LOWER}.{$workday.last_name | LOWER}@company.com
    IF $workday$in.department ne $ad$out.department
      {$workday$in.department}
    ELSE
      {$ad$out.department}
    {$corp_ad.department}
    username
    `{firstname}{lastname}`
    `{$target.username}@sample.com`
    >>[value1, value2, value3]
    organizationalStatus: ["Active", "Employee"]
    >>[Employee, Contractor, Temporary]
    organizationalStatus: ["Active", "Employee", "Contractor", "Temporary"]

    Fallback Formatters

    Configure fallback formatters for uniquely identifying attributes during identity synchronization

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    Overview

    Fallback formatters can help resolve conflicts when provisioning identities with unique attributes. This is particularly useful when automated provisioning requires unique identifiers, but the standard generated values are already in use.

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    Understanding Fallback Formatters

    When provisioning new identities through Lifecycle Management, unique attributes like usernames, login IDs, or email addresses must not conflict with existing values. Fallback formatters provide an automated way to generate alternative values when conflicts arise, ensuring provisioning can proceed without manual intervention.

    You can configure fallback formatters when configuring a to ensure new users can be onboarded efficiently, regardless of naming conflicts.

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    Use Case: Username Conflicts

    The most common use case for fallback formatters is handling username conflicts. For example:

    Your organization uses a standard username format of first initial + last name (e.g., jsmith for John Smith).

    When multiple employees have similar names, this can lead to conflicts:

    • John Smith already has jsmith

    • Jane Smith already has jsmith1

    • James Smith already has jsmith2

    When Jennifer Smith joins, the fallback formatter automatically assigns jsmith3, maintaining your naming convention while ensuring uniqueness.

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    Configuring Fallback Formatters

    Fallback formatters can be configured as part of the "Sync Identities" action within a Lifecycle Management workflow:

    1. Edit or create a Lifecycle Management policy

    2. Edit the workflow containing the Sync Identities action

    3. In the Sync Identities action configuration, click Add Fallback

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    Transformer Options for Fallback Formatters

    Several transformers can be used for implementing fallback formatters depending on your specific use case.

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    Using the NEXT_NUMBER Transformer

    A typical approach is to use the NEXT_NUMBER transformer, which is specifically designed to generate sequential numerical alternatives when naming conflicts occur.

    The NEXT_NUMBER transformer:

    • Generates a set of sequential integers as strings

    • Takes two parameters: BeginInteger (starting number) and Length (how many numbers to generate)

    • Is unique among transformers in that it returns multiple values, making it ideal for fallback scenarios

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    Other Useful Transformers for Fallbacks

    In addition to NEXT_NUMBER, other transformers can be valuable for creating fallback formatters:

    Using Random Alphanumeric for Unique Usernames:

    This could generate usernames like jsmith8f3d instead of sequential jsmith1, jsmith2, etc.

    Using UUID for Guaranteed Uniqueness:

    This would append the first 8 characters of a UUID, creating identifiers like jsmith-a7f3e9c2.

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    Implementation Example

    When configuring a fallback formatter with the NEXT_NUMBER transformer:

    1. Select the attribute that requires uniqueness (e.g., username, email)

    2. Configure the primary pattern (e.g., {first_initial}{last_name})

    3. Add a fallback using the NEXT_NUMBER transformer to generate sequential alternatives:

    This will generate up to 10 alternatives: jsmith1, jsmith2, ... jsmith10

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    Common Fallback Patterns

    Here are some commonly used fallback patterns:

    Primary Format
    Fallback Pattern
    Examples

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    How Fallback Resolution Works

    When Lifecycle Management attempts to provision a new identity with a unique attribute value that already exists:

    1. The system first tries the primary format (e.g., jsmith)

    2. If a conflict is detected, it automatically tries the first alternative using the NEXT_NUMBER transformer (e.g., jsmith1)

    3. If that value also exists, it tries the next alternative (e.g.,

    This automated conflict resolution ensures provisioning can proceed without manual intervention, even when your standard naming conventions result in conflicts.

    Configure the Transformer to use as a fallback pattern for the unique attribute that might experience conflicts
  • Close the action sidebar and save your changes to the policy.

  • jsmith2
    )
  • This process continues until either:

    • A unique value is found

    • All alternatives from the NEXT_NUMBER range are exhausted (in which case an error would be reported)

  • {first_initial}{last_name}

    {first_initial}{last_name}{NEXT_NUMBER(1, 10)}

    jsmith, jsmith1, jsmith2, etc.

    {first_name}.{last_name}

    {first_name}.{last_name}{NEXT_NUMBER(1, 10)}

    john.smith, john.smith1, john.smith2

    {username}@domain.com

    {username}{NEXT_NUMBER(1, 10)}@domain.com

    [email protected], [email protected]

    {first_name}{last_initial}

    {first_name}{last_initial}{NEXT_NUMBER(1, 10)}

    Sync Identities Action

    johns, johns1, johns2

    {first_initial}{last_name}{RANDOM_ALPHANUMERIC_GENERATOR(4)}
    {first_initial}{last_name}-{UUID_GENERATOR() | SUB_STRING,0,8}
    {first_initial}{last_name}{NEXT_NUMBER(1, 10)}

    Transformer Reference

    Reference guide for supported transformation functions and parameters for attribute transformers

    This page includes a comprehensive list of all supported transformer functions and parameters. Some commonly used transformation functions include:

    • Replacing a character with a different one

    • Removing domains from email addresses

    • Transforming to upper, lower, title, sentence, camel, or snake case

    • Using a substring from the original value

    See for more information about using attribute transformers to update or create attributes in downstream systems based on changes in your source of identity.

    hashtag
    Understanding the Attribute Transformer Interface

    When configuring attribute transformers in Lifecycle Management policies, you work with three key fields:

    hashtag
    Destination Attribute

    A Destination Attribute is a target-system attribute that Lifecycle Management creates or updates (e.g., email, username, first_name).

    Lifecycle Management uses the Destination Attribute when you build a transformer or Sync/Deprovision action. You select a Destination Attribute (from the target entity type), then supply a Formatter (a fixed value, a {source_attribute}, or a transformation pipeline). Destination Attributes can be configured for continuous sync, used by action-level or common transformers, and referenced with $target inside the same action.

    hashtag
    Formatter

    A Formatter defines the exact value or expression used to populate a target attribute (Destination Attribute) when provisioning or syncing identities.

    Formatters can be a fixed literal, a reference to a source-of-identity attribute (e.g., {first_name}), or an expression that applies transformation functions and pipelines (e.g., {email | REMOVE_DOMAIN | LOWER}).

    They're configured on transformers used by Sync/Deprovision actions and control continuous sync behavior, fallbacks, and uniqueness.

    The base transformation expression that defines how to construct the attribute value. This field can contain:

    • Source attribute references: {first_name}, {email}

    • Static text and source attributes combined: {first_name}.{last_name}@company.com

    • Static values only: "Veza"

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    Pipeline Functions

    A Pipeline Function is a chained sequence of attribute formatters that run in order using the pipe (|) operator.

    Pipeline Functions take the output of one formatter as the input to the next, letting you build multi-step transformations (for triggers, transformers, and formatter fields). They are used in workflow trigger conditions and transformer attributes to normalize, format, or compute values (for example: {department | TRIM | UPPER} or {hire_date | DATE_FORMAT, "2006-01-02"}).

    Optional transformation functions applied after the Formatter. Multiple functions are chained using the pipe (|) character, with each function's output becoming the next function's input. Examples:

    • | LOWER

    • | ASCII | REMOVE_WHITESPACE

    • | TRIM_CHARS, "." | UPPER

    At runtime, Veza combines the {Formatter}{Pipeline Functions} fields to create the complete transformation.

    hashtag
    Reading the Examples

    Each transformer below includes three types of examples:

    1. Basic Usage: Shows the transformer used alone with a simple source attribute

    2. In a Pipeline: Demonstrates chaining multiple transformers together

    3. Example: Provides practical context from Lifecycle Management scenarios

    Copy-paste these examples directly into your attribute transformer configuration, adjusting attribute names to match your source of identity.

    chevron-rightAPPENDhashtag

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    APPEND

    This transformer enables string concatenation by appending text to the end of attribute values during identity provisioning workflows.

    Parameter Format

    chevron-rightASCIIhashtag

    hashtag
    ASCII

    Removes non-printable characters and replaces non-ASCII characters with their closest ASCII equivalents. Particularly useful for Active Directory sAMAccountName and other legacy systems with strict character requirements.

    Note: The ASCII transformer performs operations on the base level, not the extended set.

    chevron-rightASSUME_TIME_ZONEhashtag

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    ASSUME_TIME_ZONE

    Interprets the incoming time string as if it were in the specified time zone, then converts it to a UTC time. (example: if the input is "1/2/2025 11pm" and the defined time zone is America/Los_Angeles the function will treat "1/2/2025 11pm" as local time in Los Angeles and output the corresponding UTC time "1/3/2025 7am")

    chevron-rightCOUNTRY_CODE_ISO3166hashtag

    hashtag
    COUNTRY_CODE_ISO3166

    Transforms country code to ISO 3166 format.

    defines codes for the representation of country names, dependent territories, and their subdivisions

    chevron-rightDATE_ADJUSThashtag

    hashtag
    DATE_ADJUST

    Adjusts date values based on hour, day, month, and year inputs. Provides full control over all time components for complex date manipulation.

    Parameter Format

    chevron-rightDATE_ADJUST_DAYhashtag

    hashtag
    DATE_ADJUST_DAY

    A convenience transformer that adjusts date values by a specified number of days only. Use this for simple day-based calculations; use DATE_ADJUST for more complex adjustments involving hours, months, or years.

    chevron-rightDATE_FORMAThashtag

    hashtag
    DATE_FORMAT

    Transforms dates to a different format using Go time layout syntax. Essential for LDAP integration and standardizing dates across systems.

    Parameter Format

    chevron-rightFIRST_Nhashtag

    hashtag
    FIRST_N

    Picks the first N characters of a string. Useful for creating shortened identifiers or initials.

    Parameter Format

    chevron-rightFROM_ENTITY_ATTRIBUTEhashtag

    hashtag
    FROM_ENTITY_ATTRIBUTE

    Looks up an entity in the Veza graph by matching an attribute value, then returns a different attribute from that entity. This is useful for cross-referencing related entities, such as finding a manager's email from an employee ID.

    Parameter Format

    chevron-rightFROM_MANY_ENTITIES_ATTRIBUTEhashtag

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    FROM_MANY_ENTITIES_ATTRIBUTE

    Looks up multiple entities in the Veza graph by matching an attribute value, then returns a specified attribute from all matching entities as a combined string. Use this when an input value may match multiple entities and you need all their values.

    Parameter Format

    chevron-rightLANGUAGE_RFC5646hashtag

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    LANGUAGE_RFC5646

    Transforms language to RFC 5646 format.

    defines "Tags for Identifying Languages." It does not contain a fixed, exhaustive list of language codes within the RFC itself. Instead, it specifies the structure and rules for constructing language tags, which are then built using codes from various external standards and registries.

    chevron-rightLAST_Nhashtag

    hashtag
    LAST_N

    Picks the last N characters of a string, where N is the number of characters to return.

    Parameter Format

    chevron-rightLEFT_PADhashtag

    hashtag
    LEFT_PAD

    Adds padding characters to the left side of a string until it reaches the specified length. Useful for creating fixed-width identifiers.

    Parameter Format

    chevron-rightLOOKUPhashtag

    hashtag
    LOOKUP

    Transforms a value using a lookup table defined in your Lifecycle Management policy. Essential for mapping codes to descriptive values or standardizing data across systems.

    Parameter Format

    chevron-rightLOWERhashtag

    hashtag
    LOWER

    Transforms all uppercase characters in a string to lowercase. One of the most commonly used transformers for normalizing usernames and email addresses.

    Parameter Format

    chevron-rightLOWER_SNAKE_CASEhashtag

    hashtag
    LOWER_SNAKE_CASE

    Transforms string to lowercase with underscores.

    Parameter Format

    chevron-rightLOWER_CAMEL_CASEhashtag

    hashtag
    LOWER_CAMEL_CASE

    Transforms a string to lower camel case (also known as dromedaryCase). The first word is lowercase, and subsequent words are capitalized with no separators.

    Parameter Format

    chevron-rightNEXT_NUMBERhashtag

    hashtag
    NEXT_NUMBER

    Generates a set of alternative values by appending sequential numbers. Essential for handling unique constraint conflicts during user provisioning. Returns an empty string first, then "2", "3", "4", etc.

    Parameter Format

    chevron-rightNEXT_NUMBER Max Lengthhashtag

    hashtag
    NEXT_NUMBER Max Length

    This transformer supports an optional maximum length parameter to simplify complex username generation workflows. It automatically evaluates combined strings (such as {first_name}_{last_name}) and truncates to specified character limits before appending numerical suffixes.

    chevron-rightNOWhashtag

    hashtag
    NOW

    Returns the current time in UTC. An optional argument indicates the outgoing time format; by default, the RFC3339 format.

    Parameter Format

    chevron-rightPHONE_NUMBER_E164hashtag

    hashtag
    PHONE_NUMBER_E164

    Transforms a phone number into the E.164 format.

    E. 164 numbers are formatted [+] [country code] [subscriber number including area code] and can have a maximum of fifteen digits. Parameter Format

    chevron-rightPREPENDhashtag

    hashtag
    PREPEND

    Adds text to the beginning of attribute values. Useful for adding prefixes like organization codes or type indicators.

    Parameter Format

    chevron-rightRANDOM_ALPHANUMERIC_GENERATORhashtag

    hashtag
    RANDOM_ALPHANUMERIC_GENERATOR

    Generates a random alphanumeric string.

    Parameter Format

    chevron-rightRANDOM_INTEGERhashtag

    hashtag
    RANDOM_INTEGER

    Generates a random integer value between specified minimum and maximum values (inclusive). Useful for creating unique test IDs or temporary identifiers. Does not require an input value.

    Parameter Format

    chevron-rightRANDOM_NUMBER_GENERATORhashtag

    hashtag
    RANDOM_NUMBER_GENERATOR

    Generates a random number string.

    Parameter Format

    chevron-rightRANDOM_STRING_GENERATORhashtag

    hashtag
    RANDOM_STRING_GENERATOR

    Generates a random string.

    Parameter Format

    chevron-rightREMOVE_CHARShashtag

    hashtag
    REMOVE_CHARS

    Removes all instances of specified characters from a string. Useful for cleaning up data and removing unwanted punctuation or special characters.

    Parameter Format

    chevron-rightREMOVE_DIACRITICShashtag

    hashtag
    REMOVE_DIACRITICS

    Removes diacritics (accents, etc.) from input string.

    Parameter Format

    chevron-rightREMOVE_DOMAINhashtag

    hashtag
    REMOVE_DOMAIN

    Removes the domain portion from an email address, leaving only the username. One of the most frequently used transformers for generating usernames from email addresses.

    Parameter Format

    chevron-rightREMOVE_WHITESPACEhashtag

    hashtag
    REMOVE_WHITESPACE

    Removes all whitespace characters (spaces, tabs, newlines) from a string. Useful for creating compact identifiers and ensuring data consistency.

    Parameter Format

    chevron-rightREPLACE_ALLhashtag

    hashtag
    REPLACE_ALL

    Replaces all instances of one string with another. Essential for character substitution and format standardization.

    Parameter Format

    chevron-rightRIGHT_PADhashtag

    hashtag
    RIGHT_PAD

    Right pads a string with a character.

    Parameter Format

    chevron-rightSENTENCE_CASEhashtag

    hashtag
    SENTENCE_CASE

    Capitalizes only the first non-whitespace character of a string and lowercases the rest. Preserves any leading whitespace. Useful for standardizing sentence-formatted text fields.

    Parameter Format

    chevron-rightSPLIThashtag

    hashtag
    SPLIT

    Splits a string and returns the string at the given index.

    Parameter Format

    chevron-rightSUB_STRINGhashtag

    hashtag
    SUB_STRING

    Extracts a substring from the original value starting at a specific position. Commonly used for creating initials or extracting portions of identifiers.

    Parameter Format

    chevron-rightTITLE_CASEhashtag

    hashtag
    TITLE_CASE

    Capitalizes the first letter of each word and lowercases the rest. Also handles dot-separated values by capitalizing the first letter of each segment. Useful for formatting names and titles.

    Parameter Format

    chevron-rightTRIMhashtag

    hashtag
    TRIM

    Removes leading and trailing whitespace from a string. Essential for cleaning up data from external systems.

    Parameter Format

    chevron-rightTRIM_CHARShashtag

    hashtag
    TRIM_CHARS

    Removes all specified characters from both the beginning and end of a string. Useful for removing padding characters or cleaning up formatted data.

    Parameter Format

    chevron-rightTRIM_CHARS_LEFThashtag

    hashtag
    TRIM_CHARS_LEFT

    Removes all specified characters from the beginning of a string only. Useful for removing leading zeros or prefixes.

    Parameter Format

    chevron-rightTRIM_CHARS_RIGHThashtag

    hashtag
    TRIM_CHARS_RIGHT

    Removes all specified characters from the end of a string only. Useful for removing trailing characters or suffixes.

    Parameter Format

    chevron-rightUPPERhashtag

    hashtag
    UPPER

    Transforms all lowercase characters in a string to uppercase. Commonly used for standardizing identifiers and codes.

    Parameter Format

    chevron-rightUPPER_CAMEL_CASEhashtag

    hashtag
    UPPER_CAMEL_CASE

    Transforms a string to upper camel case.

    Parameter Format

    chevron-rightUPPER_SNAKE_CASEhashtag

    hashtag
    UPPER_SNAKE_CASE

    Transforms string to uppercase with underscores.

    Parameter Format

    chevron-rightUTC_TO_TIME_ZONEhashtag

    hashtag
    UTC_TO_TIME_ZONE

    Interprets the incoming time string as if it were in UTC and then converts it to the specified time zone. (example: if the input is "1/2/2025 11pm" and the specified time zone is America/Los_Angeles the function will treat "1/2/2025 11pm" as the UTC time zone and output the corresponding America/Los_Angeles

    chevron-rightUUID_GENERATORhashtag

    hashtag
    UUID_GENERATOR

    Generates a UUID.

    A UUID (Universally Unique Identifier) is a 128-bit identifier used to uniquely identify information in computer systems.

    chevron-rightZERO_PADhashtag

    hashtag
    ZERO_PAD

    Adds left zero-padding to numerical string values until they reach the specified length. If the input is non-numeric, it passes through unchanged. If the numeric value is already longer than the specified length, it remains unchanged.

    Parameter Format

    or
    true
  • Conditional logic: IF statements with comparison operators

  • Characters (STRING, required)

    Basic Usage

    • Destination Attribute: email

    • Formatter: {username}

    • Pipeline Functions: | APPEND, "@company.com"

    • Result: If username = john.smith, output is [email protected]

    In a Pipeline

    • Destination Attribute: display_name

    • Formatter: {first_name}

    • Pipeline Functions: | APPEND, " " | APPEND, "{last_name}"

    • Result: If first_name = John and last_name = Smith, output is John Smith

    Example

    • Destination Attribute: user_principal_name

    • Formatter: {first_name}.{last_name}

    • Pipeline Functions: | LOWER | APPEND, "@contoso.com"

    • Use case: Generate standardized email addresses for Azure AD user provisioning

    Parameter Format

    None (no parameters required)

    Basic Usage

    • Destination Attribute: username

    • Formatter: {first_name}

    • Pipeline Functions: | ASCII

    • Result: If first_name = Łukasz, output is Lukasz

    In a Pipeline

    • Destination Attribute: login_name

    • Formatter: {first_name}.{last_name}

    • Pipeline Functions: | ASCII | LOWER | REMOVE_WHITESPACE

    • Result: If first_name = José María, last_name = García, output is josemaria.garcia

    Example

    • Destination Attribute: sAMAccountName

    • Formatter: {first_name}

    • Pipeline Functions: | ASCII | SUB_STRING, 0, 1 | LOWER

    • Use case: Generate Active Directory account names that comply with character restrictions while handling international names (converts "Łukasz" to "l")

    Parameter Format

    String - Time Zone String (Optional) - Format

    Usage Example

    Input:

    {activation_date | ASSUME_TIME_ZONE, "America/Los_Angeles"}

    {activation_date | ASSUME_TIME_ZONE, "America/Los_Angeles", "RFC3339"}

    {activation_date | ASSUME_TIME_ZONE, "-07:00"}

    {activation_date | ASSUME_TIME_ZONE, "-07:00", "RFC3339"}

    Parameter Format

    Format (STRING, optional): [alpha2, alpha3, numeric], defaults to alpha2

    Usage Example

    Input:

    {"US" | COUNTRY_CODE_ISO3166, "alpha3"}

    Output:

    USA

    Parameter
    Type
    Required
    Description

    Hours

    INTEGER

    Yes

    Number of hours to add (use negative values to subtract)

    Days

    INTEGER

    No

    Number of days to add

    Months

    INTEGER

    No

    Number of months to add

    Usage Example

    Input:

    {activation_date | DATE_ADJUST, +1, 2, 3, -1}

    Adjusts the date by adding 1 hour, 2 days, 3 months, and subtracting 1 year.

    {activation_date | DATE_ADJUST, +1, 2, 3, -1, "RFC3339"}

    {activation_date | DATE_ADJUST, +1, 2, 3, -1, "2006-01-02T15:04:05Z07:00"}

    Example

    If the input date is 2021-01-01 00:00:00 and you apply DATE_ADJUST, +1, 2, 3, -1, the output is 2020-04-03 01:00:00 (added 1 hour, 2 days, 3 months, subtracted 1 year).

    Parameter Format
    Parameter
    Type
    Required
    Description

    Days

    INTEGER

    Yes

    Number of days to add (use negative values to subtract)

    Format

    STRING

    No

    Output format (defaults to auto-detection)

    Usage Example

    Input:

    {activation_date | DATE_ADJUST_DAY, +1}

    Adds 1 day to the activation date.

    {activation_date | DATE_ADJUST_DAY, +1, "RFC3339"}

    {activation_date | DATE_ADJUST_DAY, +1, "2006-01-02T15:04:05Z07:00"}

    Example

    If the input date is 2021-01-01 00:00:00 and you apply DATE_ADJUST_DAY, +1, the output is 2021-01-02 00:00:00.

    Output Layout (STRING, required): Go time layout for output format Input Layout (STRING, optional): Go time layout for input format
    circle-exclamation

    Go Time Layout Syntax: Unlike most date formatting systems that use patterns like YYYY-MM-DD, Go uses a reference date: Mon Jan 2 15:04:05 MST 2006. Each component of this specific date represents a format element. This can be unintuitive at first, but provides unambiguous formatting.

    Understanding Go Date Format

    The reference date Mon Jan 2 15:04:05 MST 2006 breaks down as:

    Component
    Reference Value
    Meaning

    Year

    2006

    4-digit year

    Year

    06

    2-digit year

    Month

    01

    2-digit month (01-12)

    Month

    1

    Common Format Patterns

    Output Format
    Go Layout String
    Example Output

    ISO 8601 / RFC3339

    2006-01-02T15:04:05Z07:00

    2023-03-15T14:30:25-07:00

    US date

    01/02/2006

    03/15/2023

    European date

    02/01/2006

    15/03/2023

    LDAP/AD format

    20060102150405Z

    Named Format Aliases

    Instead of Go layout strings, you can use these named aliases (case-insensitive):

    Alias
    Equivalent Layout
    Example Output

    dateonly

    2006-01-02

    2023-03-15

    timeonly

    15:04:05

    14:30:25

    datetime

    2006-01-02 15:04:05

    2023-03-15 14:30:25

    kitchen

    3:04PM

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    The win32 format outputs the Windows FILETIME format used by Active Directory for attributes like accountExpires. This represents 100-nanosecond intervals since January 1, 1601 UTC.

    Basic Usage

    • Destination Attribute: hire_date

    • Formatter: {start_date}

    • Pipeline Functions: | DATE_FORMAT, "01/02/2006"

    • Result: If start_date = 2023-03-15, output is 03/15/2023

    In a Pipeline

    • Destination Attribute: formatted_date

    • Formatter: {hire_date}

    • Pipeline Functions: | DATE_FORMAT, "Jan 2, 2006" | REPLACE_ALL, " ", "_"

    • Result: If hire_date = 2023-03-15, output is Mar_15,_2023

    Using Named Aliases

    • Destination Attribute: formatted_date

    • Formatter: {hire_date}

    • Pipeline Functions: | DATE_FORMAT, "rfc3339"

    • Result: Outputs ISO 8601 format like 2023-03-15T00:00:00Z

    LDAP Z Time Format

    • Destination Attribute: accountExpires

    • Formatter: {termination_date}

    • Pipeline Functions: | DATE_FORMAT, "20060102150405Z"

    • Use case: Convert dates to LDAP Z time format (outputs UTC format like 20230315143025Z)

    Active Directory FILETIME Format

    • Destination Attribute: accountExpires

    • Formatter: {termination_date}

    • Pipeline Functions: | DATE_FORMAT, "win32"

    • Use case: Convert dates to Windows FILETIME format for AD account expiration (outputs values like 133234218250000000)

    Parsing Non-Standard Input Dates

    When your source data uses a non-standard date format, provide both the output format AND input format:

    • First parameter: desired output format

    • Second parameter: format of the input data

    For example, to convert 03-15-2023 (MM-DD-YYYY) to 2023-03-15 (ISO format):

    Length (NUMBER, required): Number of characters to return

    Basic Usage

    • Destination Attribute: initial

    • Formatter: {first_name}

    • Pipeline Functions: | FIRST_N, 1

    • Result: If first_name = John, output is J

    In a Pipeline

    • Destination Attribute: username

    • Formatter: {first_name}.{last_name}

    • Pipeline Functions: | FIRST_N, 1 | LOWER

    • Result: If first_name = John, output is j

    Example

    • Destination Attribute: username

    • Formatter: {first_name}

    • Pipeline Functions: | FIRST_N, 1 | LOWER

    • Use case: Create abbreviated usernames in the format "j.smith" by combining first initial with last name

    Parameter
    Type
    Required
    Description

    EntityType

    STRING

    Yes

    The type of graph entity to search (e.g., Employee, OktaUser, ActiveDirectoryUser)

    SourceAttribute

    STRING

    Yes

    The attribute on the entity to match against the input value

    TargetAttribute

    STRING

    Yes

    The attribute to return from the matched entity. Use id or type for built-in entity properties.

    How It Works

    1. The input value (before the |) is used as the search term

    2. The transformer finds an entity of type EntityType where SourceAttribute equals the input value

    3. It returns the TargetAttribute value from that entity

    4. If no entity is found and DefaultValue is provided, the default is returned; otherwise an error occurs

    Special Behaviors

    Scenario
    Behavior

    Empty input value

    Returns empty string "" (no error)

    Input wrapped in brackets [value]

    Brackets are automatically stripped before lookup

    TargetAttribute is id

    Returns the entity's unique graph ID

    TargetAttribute is type

    Returns the entity's type name

    No entity found, no default

    Returns error with details about the failed lookup

    Target attribute missing on entity

    Returns error (unless default provided)

    circle-info

    When used in sync workflows, this transformer checks previously computed values from the current job before querying the graph cache. This optimization prevents redundant lookups during batch operations.

    Usage Examples

    Example 1: Get manager's name from employee ID

    • Input: 12345 (an employee ID)

    • Finds: An Employee entity where employee_id = 12345

    • Returns: The manager_name attribute from that employee (e.g., Jane Smith)

    Example 2: Get department from email with a default value

    • Input: [email protected]

    • Finds: An OktaUser entity where email = [email protected]

    • Returns: The department attribute, or Unknown if no user is found

    Example 3: Chain with other transformers

    • Takes the employee ID from Workday

    • Looks up the employee's cost center

    • Converts the result to uppercase

    Example 4: Get entity's graph ID

    • Looks up an OktaUser by login

    • Returns the entity's unique graph ID (useful for subsequent lookups)

    Parameter
    Type
    Required
    Description

    EntityType

    STRING

    Yes

    The type of graph entity to search (e.g., Employee, OktaUser)

    SourceAttribute

    STRING

    Yes

    The attribute on entities to match against the input value

    TargetAttribute

    STRING

    Yes

    How It Works

    1. The input value (before the |) is used as the search term

    2. The transformer finds ALL entities of type EntityType where SourceAttribute equals the input value

    3. It collects the TargetAttribute value from each matched entity

    4. Results are joined using the separator (comma by default)

    5. If no entities are found, returns an empty string

    Special Behaviors

    Scenario
    Behavior

    Empty input value

    Returns empty string "" (no error)

    Input wrapped in brackets [value]

    Brackets are automatically stripped before lookup

    No entities found

    Returns empty string "" (no error)

    Target attribute missing on some entities

    Those entities are skipped (no error logged)

    TargetAttribute is id

    Returns the entity's unique graph ID

    TargetAttribute is type

    Returns the entity's type name

    circle-exclamation

    Unlike FROM_ENTITY_ATTRIBUTE, this transformer does not error when entities are missing the target attribute—it silently skips them. Verify your results include all expected values.

    Usage Examples

    Example 1: Get all group names for a user

    • Input: [email protected]

    • Finds: All OktaGroup entities where member_email = [email protected]

    • Returns: Engineering,Sales,All-Employees (comma-separated group names)

    Example 2: Custom separator for multi-value attributes

    • Input: 12345 (an owner ID)

    • Finds: All Application entities owned by this user

    • Returns: Slack;Salesforce;Jira (semicolon-separated)

    Example 3: Get all entity IDs

    • Finds all employees in the Engineering department

    • Returns their graph IDs as a comma-separated list

    Example 4: Get entity types

    • Looks up all identity nodes with the given email

    • Returns their type names (e.g., OktaUser,ActiveDirectoryUser,WorkdayWorker)

    Parameter Format

    None (no parameters required)

    Usage Example

    Input:

    {"Spanish" | LANGUAGE_RFC5646}

    Output:

    es

    Length (NUMBER, required)

    Usage Example

    Input:

    {"helloworld" | LAST_N, 5}

    Output:

    world

    Length (NUMBER, required): Target string length Pad (CHARACTER, optional): Character to use for padding (default is space)

    Basic Usage

    • Destination Attribute: employee_id

    • Formatter: {id}

    • Pipeline Functions: | LEFT_PAD, 5, "0"

    • Result: If id = 123, output is 00123

    In a Pipeline

    • Destination Attribute: formatted_code

    • Formatter: {cost_center}

    • Pipeline Functions: | TRIM_CHARS, "0" | LEFT_PAD, 6, "0"

    • Result: If cost_center = 001234, output is 001234 (first removes then re-applies padding)

    Example

    • Destination Attribute: employee_id

    • Formatter: {employee_id}

    • Pipeline Functions: | REMOVE_CHARS, "#" | TRIM_CHARS, "0" | LEFT_PAD, 6, "0"

    • Use case: Standardize employee IDs to 6-digit format (converts "##001234##" to "001234")

    Parameter
    Type
    Required
    Description

    TableName

    STRING

    Yes

    Name or ID of the lookup table

    ColumnName

    STRING

    Yes

    Column to search for the input value

    ReturnColumnName

    STRING

    Yes

    Column whose value to return

    How It Works

    1. The transformer first tries to match TableName against configured lookup table names

    2. If no name match is found, TableName is treated as a table ID

    3. The input value is searched in ColumnName

    4. If found, the corresponding ReturnColumnName value is returned

    5. If not found and DefaultValue is provided, the default is returned

    6. If not found and no default, an error is returned

    circle-exclamation

    Table name matching is case-sensitive. Ensure the table name in your transformer exactly matches the lookup table name defined in your policy, including capitalization.

    Special Behaviors

    Scenario
    Behavior

    Table name not found

    Falls back to treating the parameter as a table ID

    Value not found in table, default provided

    Returns the default value

    Value not found in table, no default

    Returns error with lookup details

    Other lookup errors

    Returns error with full context

    Basic Usage

    • Destination Attribute: city

    • Formatter: {location_code}

    • Pipeline Functions: | LOOKUP, "locationTable", "location_code", "city"

    • Result: If location_code = IL001 and locationTable contains that code, output is Chicago

    With Default Value

    • Destination Attribute: region

    • Formatter: {office_code}

    • Pipeline Functions: | LOOKUP, "regionTable", "code", "region_name", "Unknown Region"

    • Result: Returns mapped region name, or Unknown Region if code not in table

    In a Pipeline

    • Destination Attribute: office_email_domain

    • Formatter: {office_code}

    • Pipeline Functions: | LOOKUP, "officeTable", "code", "domain" | LOWER

    • Result: Looks up domain from table, then converts to lowercase

    Example

    • Destination Attribute: office_location

    • Formatter: {location}

    • Pipeline Functions: | LOOKUP, "locationTable", "location_code", "city"

    • Use case: Convert abbreviated location codes (like "IL001", "CA002") to full city names for user profiles, maintaining consistency across different source systems

    None (no parameters required)

    Basic Usage

    • Destination Attribute: username

    • Formatter: {first_name}

    • Pipeline Functions: | LOWER

    • Result: If first_name = JOHN, output is john

    In a Pipeline

    • Destination Attribute: email

    • Formatter: {first_name}.{last_name}@company.com

    • Pipeline Functions: | LOWER

    • Result: If first_name = John, last_name = Smith, output is [email protected]

    Example

    • Destination Attribute: login

    • Formatter: {first_name}

    • Pipeline Functions: | SUB_STRING, 0, 1 | LOWER

    • Use case: Create standardized Okta login names in format "j.smith" by extracting first initial and converting to lowercase

    None (no parameters required)

    Usage Example

    Input:

    {"Hello World" | LOWER_SNAKE_CASE}

    Output:

    hello_world

    None (no parameters required)

    Basic Usage

    • Destination Attribute: identifier

    • Formatter: {field_name}

    • Pipeline Functions: | LOWER_CAMEL_CASE

    • Result: If field_name = hello world, output is helloWorld

    In a Pipeline

    • Destination Attribute: api_field

    • Formatter: {attribute_name}

    • Pipeline Functions: | TRIM | LOWER_CAMEL_CASE

    • Result: If attribute_name = User Display Name , output is userDisplayName

    Example

    • Destination Attribute: json_property

    • Formatter: {column_name}

    • Pipeline Functions: | LOWER_CAMEL_CASE

    • Use case: Convert database column names or display names to JSON property names following JavaScript/TypeScript conventions

    Start Integer (NUMBER, required): First number in sequence Length (NUMBER, required): How many alternatives to generate

    Basic Usage

    • Destination Attribute: username

    • Formatter: {first_name}.{last_name}

    • Pipeline Functions: | LOWER | NEXT_NUMBER, 2, 3

    • Result: Generates john.smith, john.smith2, john.smith3, john.smith4 as fallback options

    In a Pipeline

    • Destination Attribute: email

    • Formatter: {first_name}{last_name}

    • Pipeline Functions: | LOWER | NEXT_NUMBER, 2, 5 | APPEND, "@company.com"

    • Result: Creates email alternatives: [email protected], [email protected], etc.

    Example

    • Destination Attribute: user_principal_name

    • Formatter: (see conditional example below)

    • Pipeline Functions: N/A (used within IF statement)

    • Use case: Intelligent username generation with length-based fallbacks:

    This handles both name length constraints and uniqueness conflicts automatically.

    Generates a set of integers as strings.

    Parameter Format

    Integer (NUMBER, required), Length (NUMBER, required)

    Usage Example

    Input:

    {"foobar" | NEXT_NUMBER, 1, 12, 4}

    Output:

    foob foo1 foo2 foo3 foo4 foo5 foo6 foo7 foo8 foo9 fo10 fo11 fo12

    String (Optional) - Format

    Usage Example

    Input:

    {NOW}

    {| NOW, "RFC3339"}

    {NOW, "RFC3339"}

    {NOW, "2006-01-02T15:04:05Z07:00"}

    Region (STRING, optional): ISO 3166-1 alpha-2 format

    Usage Example

    Input:

    {"+1-800-555-1212" | PHONE_NUMBER_E164}

    Output:

    +18005551212

    Characters (STRING, required): Text to add at the beginning

    Basic Usage

    • Destination Attribute: location_code

    • Formatter: {city_code}

    • Pipeline Functions: | PREPEND, "CORP_"

    • Result: If city_code = NYC, output is CORP_NYC

    In a Pipeline

    • Destination Attribute: contractor_username

    • Formatter: {username}

    • Pipeline Functions: | PREPEND, "c-" | LOWER

    • Result: If username = JSmith, output is c-jsmith

    Example

    • Destination Attribute: account_name

    • Formatter: {username}

    • Pipeline Functions: | PREPEND, "c-"

    • Use case: Identify contractor accounts by prefixing their usernames (converts "jsmith" to "c-jsmith" to distinguish from employee accounts)

    Length (NUMBER, required)

    Usage Example

    Input:

    {| RANDOM_ALPHANUMERIC_GENERATOR, 8}

    Output:

    a1B2c3D4

    Note: This transformer generates an alphanumeric string with eight characters.

    Min (NUMBER, required): The minimum value (inclusive) Max (NUMBER, required): The maximum value (inclusive)

    Basic Usage

    • Destination Attribute: test_id

    • Formatter: TEST

    • Pipeline Functions: | RANDOM_INTEGER, 1000, 9999

    • Result: Output is TEST followed by random number like TEST4827

    In a Pipeline

    • Destination Attribute: temp_username

    • Formatter: user

    • Pipeline Functions: | RANDOM_INTEGER, 1, 100 | APPEND, "@temp.local"

    • Result: Output like [email protected]

    Example

    • Destination Attribute: temporary_id

    • Formatter: TEST

    • Pipeline Functions: | RANDOM_INTEGER, 1000, 9999

    • Use case: Generate unique test identifiers for sandbox environments (produces values like "TEST4827", "TEST8391")

    Length (NUMBER, required)

    Usage Example

    Input:

    {| RANDOM_NUMBER_GENERATOR, 4}

    Output:

    4829

    Note: This transformer generates a random numeric string with four characters.

    Length (NUMBER, required)

    Usage Example

    Input:

    {| RANDOM_STRING_GENERATOR, 6}

    Output:

    uFkLxw

    Note: This transformer generates a random alpha string with six characters.

    Characters (STRING, required): String containing all characters to be removed

    Basic Usage

    • Destination Attribute: username

    • Formatter: {email}

    • Pipeline Functions: | REMOVE_CHARS, "@."

    • Result: If email = [email protected], output is johndoeexamplecom

    In a Pipeline

    • Destination Attribute: phone

    • Formatter: {phone_number}

    • Pipeline Functions: | REMOVE_CHARS, "()- "

    • Result: If phone_number = (123) 456-7890, output is 1234567890

    Example

    • Destination Attribute: user_id

    • Formatter: {email}

    • Pipeline Functions: | REMOVE_CHARS, "-"

    • Use case: Create clean user IDs from email addresses by removing hyphens (converts "" to "")

    None (no parameters required)

    Usage Example

    Input:

    {"José" | REMOVE_DIACRITICS}

    Output:

    Jose

    None (no parameters required)

    Basic Usage

    • Destination Attribute: username

    • Formatter: {email}

    • Pipeline Functions: | REMOVE_DOMAIN

    • Result: If email = [email protected], output is john.smith

    In a Pipeline

    • Destination Attribute: login_name

    • Formatter: {email}

    • Pipeline Functions: | REMOVE_DOMAIN | REPLACE_ALL, ".", "_"

    • Result: If email = [email protected], output is john_smith

    Example

    • Destination Attribute: username

    • Formatter: {email}

    • Pipeline Functions: | REMOVE_DOMAIN

    • Use case: Extract usernames for target systems that don't use email-style logins (converts "[email protected]" to "jsmith")

    None (no parameters required)

    Basic Usage

    • Destination Attribute: username

    • Formatter: {display_name}

    • Pipeline Functions: | REMOVE_WHITESPACE

    • Result: If display_name = John A. Doe, output is JohnA.Doe

    In a Pipeline

    • Destination Attribute: tag

    • Formatter: {department}

    • Pipeline Functions: | REMOVE_WHITESPACE | LOWER

    • Result: If department = Human Resources, output is humanresources

    Example

    • Destination Attribute: cost_center_code

    • Formatter: {cost_center}

    • Pipeline Functions: | REMOVE_WHITESPACE

    • Use case: Ensure cost center codes have no embedded spaces for system integration (converts "CC 12345" to "CC12345")

    Original (STRING, required): String to find New (STRING, required): String to replace with

    Basic Usage

    • Destination Attribute: username

    • Formatter: {display_name}

    • Pipeline Functions: | REPLACE_ALL, " ", "_"

    • Result: If display_name = John Smith, output is John_Smith

    In a Pipeline

    • Destination Attribute: identifier

    • Formatter: {employee_id}

    • Pipeline Functions: | REPLACE_ALL, "-", "" | TRIM

    • Result: If employee_id = EMP-12345, output is EMP12345

    Example

    • Destination Attribute: email

    • Formatter: {email}

    • Pipeline Functions: | REPLACE_ALL, " ", "."

    • Use case: Fix malformed email addresses with spaces (converts "john " to "")

    Length (NUMBER, required),

    Pad (CHARACTER, optional): Default is space

    Usage Example

    Input:

    {"123" | RIGHT_PAD, 5, "0"}

    Output:

    12300

    None (no parameters required)

    Basic Usage

    • Destination Attribute: description

    • Formatter: {notes}

    • Pipeline Functions: | SENTENCE_CASE

    • Result: If notes = THE QUICK BROWN FOX, output is The quick brown fox

    In a Pipeline

    • Destination Attribute: formatted_notes

    • Formatter: {comment}

    • Pipeline Functions: | TRIM | SENTENCE_CASE

    • Result: If comment = IMPORTANT MESSAGE HERE , output is Important message here

    Example

    • Destination Attribute: job_description

    • Formatter: {job_title}

    • Pipeline Functions: | SENTENCE_CASE

    • Use case: Normalize job descriptions from all-caps source data to sentence case for cleaner display

    Split String (STRING, required), Index (NUMBER, required)

    Usage Example

    Input:

    {"[email protected]" | SPLIT, "@", 0}

    Output:

    first.last

    Note: This transformer returns the results where the index starts at zero (0).

    Offset (NUMBER, required): Starting position (0-based index) Length (NUMBER, required): Number of characters to extract

    Basic Usage

    • Destination Attribute: initial

    • Formatter: {first_name}

    • Pipeline Functions: | SUB_STRING, 0, 1

    • Result: If first_name = John, output is J

    In a Pipeline

    • Destination Attribute: short_id

    • Formatter: {employee_id}

    • Pipeline Functions: | SUB_STRING, 3, 4 | UPPER

    • Result: If employee_id = EMP12345, output is 1234

    Example

    • Destination Attribute: username

    • Formatter: {first_name}

    • Pipeline Functions: | SUB_STRING, 0, 1 | LOWER

    • Use case: Generate usernames like "j.smith" by extracting first initial and combining with last name

    None (no parameters required)

    Basic Usage

    • Destination Attribute: display_name

    • Formatter: {full_name}

    • Pipeline Functions: | TITLE_CASE

    • Result: If full_name = john doe, output is John Doe

    In a Pipeline

    • Destination Attribute: formatted_name

    • Formatter: {name}

    • Pipeline Functions: | TRIM | TITLE_CASE

    • Result: If name = JANE SMITH , output is Jane Smith

    Example

    • Destination Attribute: display_name

    • Formatter: {username}

    • Pipeline Functions: | TITLE_CASE

    • Use case: Format dot-separated usernames for display (converts "john.doe" to "John.Doe")

    None (no parameters required)

    Basic Usage

    • Destination Attribute: username

    • Formatter: {display_name}

    • Pipeline Functions: | TRIM

    • Result: If display_name = " John Doe ", output is John Doe

    In a Pipeline

    • Destination Attribute: email

    • Formatter: {email_address}

    • Pipeline Functions: | TRIM | LOWER

    • Result: If email_address = " [email protected] ", output is [email protected]

    Example

    • Destination Attribute: display_name

    • Formatter: {display_name}

    • Pipeline Functions: | TRIM

    • Use case: Clean up imported user data that may have padding whitespace from CSV files or database fields

    Characters (STRING, required): String containing all characters to remove from both ends

    Basic Usage

    • Destination Attribute: employee_id

    • Formatter: {id_number}

    • Pipeline Functions: | TRIM_CHARS, "0."

    • Result: If id_number = 000.123.000, output is 123

    In a Pipeline

    • Destination Attribute: clean_code

    • Formatter: {code}

    • Pipeline Functions: | TRIM_CHARS, "-_" | UPPER

    • Result: If code = ---ABC123___, output is ABC123

    Example

    • Destination Attribute: office_code

    • Formatter: {office_code}

    • Pipeline Functions: | TRIM_CHARS, ".0" | TRIM_CHARS_RIGHT, ".USCA"

    • Use case: Clean up office codes with variable padding (converts "000.8675309.USCA" to "8675309")

    Characters (STRING, required): String containing all characters to remove from the beginning

    Basic Usage

    • Destination Attribute: cost_center

    • Formatter: {cost_center_code}

    • Pipeline Functions: | TRIM_CHARS_LEFT, "0"

    • Result: If cost_center_code = 00012345, output is 12345

    In a Pipeline

    • Destination Attribute: identifier

    • Formatter: {raw_id}

    • Pipeline Functions: | TRIM_CHARS_LEFT, "x" | UPPER

    • Result: If raw_id = xxxABC123, output is ABC123

    Example

    • Destination Attribute: cost_center

    • Formatter: {cost_center}

    • Pipeline Functions: | TRIM_CHARS_LEFT, "0"

    • Use case: Remove leading zeros from cost center codes while preserving trailing zeros (converts "00012345" to "12345")

    Characters (STRING, required): String containing all characters to remove from the end

    Basic Usage

    • Destination Attribute: office_code

    • Formatter: {raw_office_code}

    • Pipeline Functions: | TRIM_CHARS_RIGHT, "0"

    • Result: If raw_office_code = ABC12300, output is ABC123

    In a Pipeline

    • Destination Attribute: clean_code

    • Formatter: {code}

    • Pipeline Functions: | TRIM_CHARS_RIGHT, "temp" | UPPER

    • Result: If code = ABC123temp, output is ABC123

    Example

    • Destination Attribute: office_code

    • Formatter: {office_code}

    • Pipeline Functions: | TRIM_CHARS_RIGHT, "0"

    • Use case: Remove trailing zeros from office codes while preserving leading zeros (converts "ABC12300" to "ABC123")

    None (no parameters required)

    Basic Usage

    • Destination Attribute: department_code

    • Formatter: {department}

    • Pipeline Functions: | UPPER

    • Result: If department = sales, output is SALES

    In a Pipeline

    • Destination Attribute: user_id

    • Formatter: {username}

    • Pipeline Functions: | REMOVE_WHITESPACE | UPPER

    • Result: If username = john smith, output is JOHNSMITH

    Example

    • Destination Attribute: last_name_normalized

    • Formatter: {name}

    • Pipeline Functions: | UPPER

    • Use case: Standardize employee last names for matching across systems (converts "Smith" to "SMITH")

    None (no parameters required)

    Usage Example

    Input:

    {"hello world" | UPPER_CAMEL_CASE}

    Output:

    HelloWorld

    None (no parameters required)

    Usage Example

    Input:

    {"hello world" | UPPER_SNAKE_CASE}

    Output:

    HELLO_WORLD

    time "1/2/2025 3pm") Note: When using the time zone parameter, a named time zone (
    America/Los_Angeles
    ) accounts for daylight saving time, whereas a time zone offset (
    -07:00
    ) is always calculated from UTC, ignoring daylight saving time.

    Parameter Format

    String - Time Zone String (Optional) - Format

    Usage Example

    Input:

    {activation_date | UTC_TO_TIME_ZONE, "America/Los_Angeles"}

    {activation_date | UTC_TO_TIME_ZONE, "America/Los_Angeles", "RFC3339"}

    {activation_date | UTC_TO_TIME_ZONE, "-07:00"}

    {activation_date | UTC_TO_TIME_ZONE, "-07:00", "RFC3339"}

    Parameter Format

    None (no parameters required)

    Usage Example

    Input:

    {| UUID_GENERATOR}

    Output:

    123e4567-e89b-12d3-a456-426614174000

    Length (NUMBER, required): Target string length for zero-padding

    Basic Usage

    • Destination Attribute: employee_id

    • Formatter: {id}

    • Pipeline Functions: | ZERO_PAD, 6

    • Result: If id = 1234, output is 001234

    Example

    • Destination Attribute: badge_number

    • Formatter: {badge_id}

    • Pipeline Functions: | ZERO_PAD, 6

    • Use case: Standardize badge numbers to 6-digit format for access control systems (converts "1234" to "001234", leaves "12345678" unchanged, and passes non-numeric values like "admin" through unchanged)

    Attribute Transformers
    ISO 3166arrow-up-right
    RFC 5646arrow-up-right
    {date_field | DATE_FORMAT, "2006-01-02", "01-02-2006"}
    {start_date | DATE_FORMAT, "2006-01-02", "01-02-2006"}
    {12345 | FROM_ENTITY_ATTRIBUTE, "Employee", "employee_id", "manager_name"}
    {[email protected] | FROM_ENTITY_ATTRIBUTE, "OktaUser", "email", "department", "Unknown"}
    {$workday.employee_id | FROM_ENTITY_ATTRIBUTE, "Employee", "id", "cost_center" | UPPERCASE}
    {john.smith | FROM_ENTITY_ATTRIBUTE, "OktaUser", "login", "id"}
    {[email protected] | FROM_MANY_ENTITIES_ATTRIBUTE, "OktaGroup", "member_email", "name"}
    {12345 | FROM_MANY_ENTITIES_ATTRIBUTE, "Application", "owner_id", "app_name", ";"}
    {Engineering | FROM_MANY_ENTITIES_ATTRIBUTE, "Employee", "department", "id"}
    {[email protected] | FROM_MANY_ENTITIES_ATTRIBUTE, "Identity", "email", "type"}
    IF sys_attr__would_be_value_len le 20
      {first_name | LOWER}.{last_name | LOWER | NEXT_NUMBER, 2, 3}
    ELSE IF sys_attr__would_be_value_len le 30
      {first_name | LOWER}.{last_name | LOWER | FIRST_N, 1 | NEXT_NUMBER, 2, 3}
    ELSE
      {first_name | LOWER | FIRST_N, 1}.{last_name | LOWER | FIRST_N, 1 | NEXT_NUMBER, 2, 3}

    Years

    INTEGER

    No

    Number of years to add

    Format

    STRING

    No

    Output format (defaults to auto-detection)

    1 or 2-digit month (1-12)

    Month

    Jan

    3-letter abbreviation

    Month

    January

    Full month name

    Day

    02

    2-digit day (01-31)

    Day

    2

    1 or 2-digit day (1-31)

    Day

    _2

    Space-padded day

    Hour

    15

    24-hour format (00-23)

    Hour

    03 or 3

    12-hour format (01-12 or 1-12)

    Minute

    04

    Minutes (00-59)

    Second

    05

    Seconds (00-59)

    AM/PM

    PM

    Uppercase AM/PM

    AM/PM

    pm

    Lowercase am/pm

    Timezone

    MST

    Timezone abbreviation

    Timezone

    -0700

    Numeric offset

    Timezone

    Z0700

    Z for UTC, offset otherwise

    20230315143025Z

    Human readable

    Jan 2, 2006

    Mar 15, 2023

    Full datetime

    January 2, 2006 3:04 PM

    March 15, 2023 2:30 PM

    Date only

    2006-01-02

    2023-03-15

    Time only

    15:04:05

    14:30:25

    2:30PM

    rfc822

    02 Jan 06 15:04 MST

    15 Mar 23 14:30 PDT

    rfc822z

    02 Jan 06 15:04 -0700

    15 Mar 23 14:30 -0700

    rfc850

    Monday, 02-Jan-06 15:04:05 MST

    Wednesday, 15-Mar-23 14:30:25 PDT

    rfc1123

    Mon, 02 Jan 2006 15:04:05 MST

    Wed, 15 Mar 2023 14:30:25 PDT

    rfc1123z

    Mon, 02 Jan 2006 15:04:05 -0700

    Wed, 15 Mar 2023 14:30:25 -0700

    rfc3339

    2006-01-02T15:04:05Z07:00

    2023-03-15T14:30:25-07:00

    rfc3339nano

    2006-01-02T15:04:05.999999999Z07:00

    2023-03-15T14:30:25.123456789-07:00

    ansic

    Mon Jan _2 15:04:05 2006

    Wed Mar 15 14:30:25 2023

    unixdate

    Mon Jan _2 15:04:05 MST 2006

    Wed Mar 15 14:30:25 PDT 2023

    rubydate

    Mon Jan 02 15:04:05 -0700 2006

    Wed Mar 15 14:30:25 -0700 2023

    stamp

    Jan _2 15:04:05

    Mar 15 14:30:25

    stampmilli

    Jan _2 15:04:05.000

    Mar 15 14:30:25.123

    stampmicro

    Jan _2 15:04:05.000000

    Mar 15 14:30:25.123456

    stampnano

    Jan _2 15:04:05.000000000

    Mar 15 14:30:25.123456789

    layout

    01/02 03:04:05PM '06 -0700

    03/15 02:30:25PM '23 -0700

    win32

    Active Directory FILETIME

    133234218250000000

    DefaultValue

    STRING

    No

    Value to return if no matching entity is found

    The attribute to return from all matched entities. Use id or type for built-in entity properties.

    Separator

    STRING

    No

    Character(s) to join multiple results (defaults to ,)

    Result ordering

    Results appear in graph discovery order (not guaranteed to be consistent)

    DefaultValue

    STRING

    No

    Value to return if lookup fails

    [email protected]envelope
    [email protected]envelope
    [email protected]envelope
    [email protected]envelope