Workflow Data Fabric Lifecycle

  • Freigeben Version: Australia
  • Aktualisiert 12. März 2026
  • 2 Minuten Lesedauer
  • Workflow Data Fabric operates through four distinct phases that separate planning, access, governance, and consumption. Each phase addresses specific activities and involves distinct roles working in dedicated surfaces.

    Abbildung : 1. Workflow Data Fabric Lifecycle
    Infographic showing the lifecycle: Prepare, Connect, Understand, Act

    Prepare

    The Prepare phase addresses what exists that might meet your needs. Workflow Data Fabric Home provides an AI-guided entry point where natural language queries surface relevant assets. The Data Catalog functions as a marketplace where you explore existing Data Products and Data Interfaces, evaluating them through trust scores, lineage visualization, and metadata quality. This exploration helps you decide whether to reuse existing assets, connect new data sources, or build new data products.

    Roles: WDF Consumers and WDF Builders

    Where: Workflow Data Fabric Home for guided search; Data Catalog for detailed exploration

    Why: Helps prevent duplicate work and enables informed decisions through comprehensive asset visibility

    For more information, see Ask Now Assist for Workflow Data Fabric for recommendations.

    Connect

    A connection represents the boundary between ServiceNow and external systems. This phase establishes secure pathways to external data sources and configures how ServiceNow discovers their metadata.

    Install and configure spokes, Integration Hub connectors, and MCP servers for your target systems in Connect Hub. Set up credentials, authentication, and access controls. Create and configure metadata collectors that scan these systems to populate the Data Catalog. These collectors are created here but execute during the Understand phase.

    Roles: Connection Admins establish and maintain connections; WDF Builders create custom integration components

    Where: Connect Hub

    Why: Provides secure, governed access to external data sources while enabling automated metadata discovery

    For more information, see Connect to external systems.

    Understand

    In the Understand phase, you convert raw connectivity into governed, reusable data. The metadata track executes automatically as collectors populate the Data Catalog with schemas, lineage, and governance signals. Simultaneously, the contract track involves deliberate authoring of data access patterns.

    Metadata collectors execute automatically, populating the Data Catalog with discovered schemas, lineage, and governance metadata. Data Stewards curate this catalog. In Data Workbench, Data Stewards author Data Interfaces that define stable contracts for data access, supporting single table, JOIN, and UNION patterns. They package these interfaces into Data Products with business context, documentation, and access controls.

    Role: Data Stewards curate discovered metadata and author all contracts

    Where: Data Workbench for contract authoring; Data Catalog for metadata curation

    Why: Creates backward-compatible contracts that abstract source system complexity while maintaining comprehensive metadata

    For more information, see Build data assets.

    Act

    The Act phase represents the consumption layer where governed data powers business outcomes. The Data Catalog shifts from a curation tool to a discovery and access portal. Users build workflows, analytics, and AI experiences that consume data exclusively through Data Interface contracts.

    Discover published Data Products in the Data Catalog and request access through governance workflows. Verify lineage before using. Build workflows in Flow Designer, create dashboards in Performance Analytics, or enable AI agents—all consuming data through the stable Data Interface contracts. Metadata collectors continuously refresh the catalog as Data Products evolve, keeping documentation and lineage current.

    Roles: WDF Consumers discover and request access; WDF Operators build workflows and experiences

    Where: Data Catalog for discovery and access; Data Workbench supports maintenance activities

    Why: Delivers business value while preserving governance boundaries and data quality

    For more information, see .