Exploring Workflow Data Fabric Hub
Summarize
Summary of Exploring Workflow Data Fabric Hub
Workflow Data Fabric Hub enables ServiceNow customers to unify business and technology data from multiple external sources, providing centralized, real-time access to enterprise data without physically copying it into their ServiceNow instance. This capability supports seamless data integration from external warehouses, lakes, and databases such as Snowflake, Google BigQuery, Amazon Redshift, Databricks, and Oracle.
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By creating zero copy connections and data fabric tables, the hub allows users to access and utilize external data in real time, fueling AI agents, workflows, and analytics on the ServiceNow AI Platform. This approach enhances workflow automation and enriches metrics by leveraging enterprise data directly from its source.
Key Features
- Zero Copy Connections: Securely connect to external data sources without copying data into the ServiceNow instance, ensuring real-time access and reducing data redundancy.
- Data Fabric Tables: Virtual tables that represent external data, allowing data consumers and applications to interact with external datasets as if they were stored locally.
- Role-based Usage:
- Connection Admin: Manages secure connections and credentials with external data sources.
- Data Steward: Creates and maintains data fabric tables, ensuring data quality and business alignment.
- Data Consumer: Accesses data fabric tables to develop applications and define data requirements.
Typical Workflow
The process involves collaboration among data consumers, data stewards, connection admins, and data source admins:
- Data consumers and stewards define data needs for new applications.
- Connection admins establish secure zero copy connections using service accounts provided by data source admins.
- Data stewards create data fabric tables by mapping external schemas and columns.
- Data consumers develop applications accessing real-time external data seamlessly.
- Data source admins monitor and communicate schema changes to maintain data consistency.
Benefits
- Real-time Data Access: Instantly access external data without duplication, reducing storage and latency.
- Virtual Data Representation: Make external data appear as local tables for ease of use in applications.
- Improved Data Governance: Roles and responsibilities ensure secure, quality data access and management.
When to Use Workflow Data Fabric Hub vs Integration Hub
- Use Workflow Data Fabric Hub for real-time, zero-copy data retrieval from external systems.
- Use Integration Hub when advanced data import, transformation, or customizable integrations are required.
Next Steps
ServiceNow customers interested in leveraging Workflow Data Fabric Hub should explore configuration guides, management of zero copy connections, creating and maintaining data fabric tables, and how to access real-time external data in their applications to fully utilize this feature.
Discover how Workflow Data Fabric Hub unifies business and technology data from multiple sources, enabling centralized, real-time access to your enterprise data without copying it to your instance.
Workflow Data Fabric Hub overview
Workflow Data Fabric Hub provides a view where you can browse data source connectors, establish connections, and create data fabric tables that provide access to data from external sources.
- Access enterprise data from external data warehouses including Snowflake, Google BigQuery, and Amazon Redshift, data lakes such as Databricks, and databases including Oracle.
- Retrieve data from external sources in real time without copying any data to your instance using zero copy connections.
- Fuel AI agents and workflows on the ServiceNow AI Platform with external data using data fabric tables.
- Provide data to AI-powered features on the ServiceNow AI Platform, expand workflow automation, and enrich metrics and analytics with enterprise data.
Workflow Data Fabric users
| User | Description |
|---|---|
| Connection admin | Establishes secure connections to external data sources by coordinating with data source administrators, managing connection credentials, and maintaining data access. |
| Data steward | Creates data fabric tables that provide access to external data, and maintains data quality to meet the business needs of data consumers. |
| Data consumer | Accesses data fabric tables to develop applications. Defines an application's data requirements and coordinates with the data steward to refine data. |
End-to-end workflow
This infographic shows a sample end-to-end workflow of different users working together to gather requirements, establish a zero copy connection, and create a data fabric table in Workflow Data Fabric Hub.
In this workflow:
- A data consumer meets with a data steward and the connection admin to discuss data requirements for a new application on the ServiceNow AI Platform.
- The connection admin gathers the data requirements and meets with the data source admin to create a service account that can access the schema and tables needed for the new application.
- The connection admin establishes a secure connection to the external data lake in the Workflow Data Fabric Hub using the service account credentials provided by the data source admin.
- The connection admin configures access controls in the connection details, ensuring the data steward can access the connection to view data assets in the external data lake and create a data fabric table.
- The data steward selects the established connection in the Workflow Data Fabric Hub and creates a data fabric table.
- The data steward explores the available schema, selects a source table with the required data, and maps columns between the source table and the data fabric table.
- The data steward works with the data consumer to review the data fabric table and ensure that it meets the business needs of the application.
- The data consumer begins developing the new application and accesses the data fabric table and its external data in real time just like any table on the ServiceNow AI Platform.
- The data source admin monitors the external schema for consistency and communicates future schema changes to the connection admin and data steward.
Workflow Data Fabric Hub benefits
| Benefit | Feature | Users |
|---|---|---|
| Access real-time data from external sources directly, without copying any data to your instance. | Zero copy connections | Connection admin |
| Create a virtual representation of data from an outside source and make it accessible to data consumers on the instance as if it's stored locally. | Data fabric tables | Data steward, data consumer |
| Map internal or external data to a predefined data fabric table in an application using a zero copy connection. | Data fabric tables included with applications | Instance admin, connection admin, data steward |
Differences between Workflow Data Fabric Hub and Integration Hub
Choose whether to use Workflow Data Fabric Hub or Integration Hub to integrate with external systems.
- When you want to retrieve real-time data from external sources without storing it on your instance, use Workflow Data Fabric Hub.
- When you want advanced import and transformation options or customizable integrations, use Integration Hub.