Data Transformation

Policy-based Transforms

Define attribute mappings, transformations, and business rules with a safe transform engine and declarative rules. No eval, no arbitrary code — just whitelisted functions and confidence-based resolution.

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Core Capabilities

Attribute Mapping

Map attributes between systems with different schemas. Rename fields, combine values, split attributes, and apply format conversions automatically.

Confidence Scoring

Each flow rule assigns a confidence score (0-100) to its output. When multiple connectors contribute to the same attribute, the highest-confidence value wins automatically.

Four Rule Types

Join rules correlate identities. Flow rules map attributes. Projection rules control exports. MeshComposer rules enrich mesh objects with computed values.

Policy Examples

See how transform policies are defined in Identity Mesh

Join Rule

Join Rule: "Match by Employee ID"
  Connector: Corporate AD
  Source Attribute: employeeID
  Target Attribute: EmployeeId
  Join Type: Exact Match

  // When an imported AD user has employeeID = "12345",
  // it joins to the mesh object with EmployeeId = "12345"

Flow Rule (Inbound)

Flow Rule: "Import AD Display Name"
  Connector: Corporate AD
  Direction: Inbound
  Source: displayName
  Target: DisplayName
  Confidence: 80
  TransformScript: Concat(Left(givenName, 1), ". ", sn)

  // Transforms "John Smith" → "J. Smith"
  // Confidence 80 means this value wins over
  // sources with lower confidence

Projection Rule (Outbound)

Projection Rule: "Provision to HR DB"
  Target Connector: HR Database
  Object Type: User
  Filter: department != "Contractors"
  Container: dbo.Employees

  // Only non-contractor users are projected
  // to the HR Database connector's export queue

MeshComposer Rule

MeshComposer Rule: "Generate Username"
  Target Attribute: SamAccountName
  TransformScript: ToLower(Concat(Left(FirstName, 1), LastName))
  Confidence: 90

  // Composes "jsmith" from FirstName="John", LastName="Smith"
  // Runs during mesh object composition

Built-in Functions

Whitelisted transform functions available in TransformScript expressions

String Functions

ToUpper, ToLower, Trim
Concat, Replace, Substring
Left, Right, Split, Join

Date & Utility Functions

Now, Format
Coalesce (first non-null value)

Logical Functions

If (conditional value)
Switch (multi-branch selection)

Use Cases

Schema Normalization

Different systems use different schemas. Transform policies normalize attribute names, formats, and values so every system speaks the same language.

Role-based Access

Use conditional transforms to assign group memberships, permissions, and entitlements based on department, title, location, or any combination of attributes.

Data Cleansing

Validate, sanitize, and standardize identity data as it flows between systems. Catch errors before they propagate and enforce data quality rules.

Compliance Enforcement

Filter sensitive attributes, mask PII data, and enforce data residency rules through transform policies that run automatically on every sync operation.

Ready to Transform Your Identity Data?

See how policy-based transforms can normalize and govern identity data across your enterprise.

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