--- sourceDocument: Australia Workflow Data Fabric sourceDocumentLink: https://www.servicenow.com/docs/r/australia/integrate-applications Release : - australia ft:locale : - en-US ft:publication_title : - Australia Workflow Data Fabric ft:clusterId : - crint bundleId : - crint workflow : - Creator --- # Data interfaces # Data interfaces {#ariaid-title1} Release version: Australia Updated March 25, 2026 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of Data interfaces Data interfaces in ServiceNow provide a stable, governed contract for querying data from single or multiple sources, including ServiceNow tables and external systems. They define a consistent schema with fixed field names and data types, insulating consumers---such as dashboards, workflows, and applications---from disruptions caused by changes in underlying data sources. This stability ensures long-term reliability and ease of integration. Show full answer Show less ## How Data Interfaces Work A data interface maps source data to a target schema that consumers query without needing to know the underlying source details. It can expose data from one table, or combine multiple tables using JOIN or UNION operations. The interface manages source connections, applies column mappings, and returns data in the defined schema, enabling seamless and consistent data access. ## Combination Methods * **Single table:** Provides controlled access to one source table with consistent naming and documentation---ideal when no data combination is necessary. * **JOIN:** Supports INNER JOIN to combine related data from multiple tables based on matching columns, useful for merging complementary datasets like customer and order information. * **UNION:** Stacks rows from multiple tables with similar structures into a unified result, suitable for consolidating data across regions or systems. ## Schema Stability Once published, data interfaces maintain their schema permanently, even if underlying source tables change. This permanence prevents breaking changes in dependent dashboards and workflows. Adding new columns to interfaces does not disrupt existing queries, allowing consumers to retrieve both original and new data seamlessly. ## Relation to Data Products While data interfaces can be queried directly, they are often packaged within data products that provide additional metadata, documentation, and access controls. A single interface can be included in multiple data products to serve different business needs, such as Customer 360 and Sales Analytics. ## Accessing External Data Data interfaces can integrate external data via Data Fabric Tables, which enable zero-copy querying of external databases like Snowflake, Databricks, and Oracle while leaving data in the source system. When using JOIN or UNION with Data Fabric Tables, intermediate implementation tables are created but remain hidden from consumers. ## Querying Data Interfaces Consumers can access data interfaces through various methods tailored to different use cases: * Flow Designer for automated workflows * Dashboard Builder for visual reports and analytics * APIs for integration within applications and scripts * AI Data Explorer for natural language queries Data interfaces provide stable contracts for accessing data from single tables or combined sources through JOIN or UNION operations. A data interface defines the schema, field names, and data types that consumers use to query data. Interfaces act as stable access layers between consumers and underlying data sources. When source systems change, the data interface schema remains consistent and protects dashboards, workflows, and applications from breaking changes. ## How data interfaces work Data interfaces map source data to a target schema that consumers query. The data interface defines which columns appear, their names, and their data types. A data interface can expose data from a single ServiceNow table, a single Data Fabric Table connected to an external system, or multiple sources combined through JOIN or UNION operations. Consumers query the data interface without requiring knowledge about which source systems provide the data. The data interface handles connections to sources, applies column mappings, and returns results in the defined schema. ## Combination methods {#data-interfaces__table_combination__entry__3} | Method | Description | When to use | |-|-|-| | Single table | Exposes one source table through a governed interface with consistent naming and documentation. | Provide controlled access to a ServiceNow tables or external tables when no combination is required. | | JOIN | Combines related data from multiple tables based on matching column values. The current release supports INNER JOIN operations. | Merge customer data with order data, match purchase orders with approval records, or create comprehensive entity views across systems. | | UNION | Stacks rows from multiple tables with similar structures into one unified result. The current release supports UNION operations. | Combine data from multiple regions, aggregate similar data across systems, or consolidate records from different sources. | [Table 1. Combination methods] {#data-interfaces__table_combination} ## Schema stability Data interfaces provide schema permanency. After publication, the data interface maintains its structure even when underlying source tables change. This stability protects consumers from breaking changes. A dashboard built on a data interface continues working when you upgrade or replace a source system. Workflows that query a data interface don't break when column names change in source tables. When you extend a data interface by adding new columns, existing queries continue working. Consumers retrieve only the columns they originally queried, plus any new columns they choose to include. ## Data interfaces and data products You can query data interfaces directly from workflows or dashboards. More commonly, data products package interfaces and provide additional metadata, documentation, and access controls. Multiple data products can include a single interface. For example, a Customer Profile interface might be part of a Customer 360 data product and also included in a Sales Analytics data product. ## Data interfaces and external sources Data interfaces can access external data through Data Fabric Tables. These tables provide zero-copy access to external databases such as Snowflake, Databricks, and Oracle. Data stays in the source system but can be queried through ServiceNow. When you create a data interface using JOIN or UNION with Data Fabric Tables, the system generates intermediate tables for the operation. These intermediate tables are implementation details that remain hidden from the Data Catalog. Consumers interact only with the published interface. ## Querying data interfaces Consumers access data interfaces through multiple channels: * Flow Designer for building automated workflows * Dashboard Builder for creating visualizations and reports * APIs for programmatic access from applications and scripts * AI Data Explorer for natural language queries ## What to explore next To learn more about data interfaces, see: * [Managing data interfaces](https://www.servicenow.com/docs/2YbI1rxrOXVsXcuMrb3BPg "Create a data interface to control how source data is filtered, combined, and exposed to consumers as a stable, governed schema.") * [Managing data products](https://www.servicenow.com/docs/kntJg65ICY6tvRGZEEOPDA "Create, publish, and promote data products to make governed data available to consumers in your organization.")