It sounds simple, but in most enterprise environments, accessing data with full business context is a challenge. Your data lives across applications, data platforms, teams, and processes. It often carries different definitions, formats, and levels of context depending on where it sits and how it is used. Bringing it all together in a flexible data foundation that provides the context AI agents need to reason, respond, and act across business workflows is critical. That foundation is often a business data fabric, which leverages data products to safely consume and analyze data in any application, including agentic AI.

Data products are pre-configured, governed, curated data sets that can be shared and reused across your organization for various use cases, including reporting, analytics, AI applications, and more. Here we’ll talk about three ways SAP helps deliver semantically rich data: through SAP-managed data products, customer-owned data products, and open ecosystem sharing across SAP and partner data environments.

1. SAP-managed data products: A good starting point

SAP applications contain some of your organization’s most important business data. Finance, supply chain, procurement, HR, sales, and customer processes are often deeply connected to SAP applications, such as SAP S/4HANA, SAP Ariba, and SAP SuccessFactors. SAP-managed data products can bring together related information from multiple SAP applications while retaining the relationships and definitions that make the data useful.

That context is captured in and delivered to users through SAP-managed data products. SAP-managed data products provide ready-to-use data in the form of a data product designed using our deep expertise and knowledge of data architecture within SAP systems. SAP maintains the governance, security, and quality of managed data products over their lifecycle so that you can focus on other unique and strategic data needs.

SAP-managed data products are readily available to discover and use in the SAP Business Data Cloud catalog.

2. Customer-owned data products: For your unique needs

SAP-managed data products are an important starting point, but every business has its own definitions, priorities, and ways of working. Data may reside outside of SAP applications, and you need the ability to create your own data products to make it useful.

With SAP Business Data Cloud, customers can create their own data products that reflect their unique business logic, capturing that meaning and making it available across analytics, planning, and AI use cases. Instead of creating one-off data models for individual reports or projects, teams can build reusable data products that carry consistent definitions and business context.

An agent asked to explain a working capital trend, identify a supply chain issue, or support a planning decision needs to understand the organization’s version of the truth. Customer-owned data products help make that possible by encoding business-specific semantics into data assets that can be reused across the enterprise.

3. Open ecosystems: Connecting data environments

Most businesses operate in a multi-cloud world with a mix of SAP and non-SAP applications, data lakes, data warehouses, and AI or machine learning platforms. This scenario makes openness to sharing data across a heterogeneous environment essential.

SAP Business Data Cloud supports an open data ecosystem through SAP Business Data Cloud Connect and its partnerships with third-party platforms such as Databricks and Snowflake.

The goal is to help organizations share SAP and non-SAP data across environments while preserving business context. With bidirectional, zero-copy sharing, data products can be made available across SAP and partner platforms without requiring teams to move or duplicate data constantly.

By supporting zero-copy sharing, SAP helps organizations work with data where it lives while still making it available for advanced use cases. For example, teams can use SAP Databricks to apply machine learning, forecasting, or data science techniques to SAP data products, then bring those enriched outputs back into SAP Business Data Cloud. Those outputs can then support analytics, planning, and agentic AI scenarios.

The same principle applies to open data ecosystem sharing with SAP Snowflake. SAP and partner data environments can work together while maintaining the semantic context that makes business data useful.

A stronger data foundation for agentic AI

Agentic AI has fundamentally changed how business users interact with enterprise systems. Agents can help answer questions, surface insights, recommend actions, and support business processes across functions. But the potential of AI still depends on the quality and context of the data underneath.

SAP Business Data Cloud helps address that challenge by making semantically rich data available in multiple ways. SAP-managed data products provide a trusted foundation based on SAP’s understanding of business applications. Customer-owned data products let organizations extend that foundation with their own definitions and business logic. Its open data ecosystem connects SAP and partner data environments so data can be enriched and reused without losing meaning.

Together, these capabilities help create the kind of data foundation AI agents need to deliver business transformation.

To learn more and see a demonstration, watch the on-demand webinar, How to Accelerate Agentic AI with an Open Data Ecosystem.