This week at SAP TechEd Berlin, we announced new lakehouse and business data fabric capabilities to help enterprises build AI agents act with greater autonomy and confidence.
As AI is deployed across business processes, effective decision-making now hinges on unifying fragmented data and business context. AI agents can generate results quickly, but good judgement depends on deep understanding of how an organization runs. They need access to data across the enterprise, trusted views of business entities, and an understanding of the relationships, processes, and rules that define how the business operates.
SAP Business Data Cloud (SAP BDC) is the trusted data foundation for SAP Business AI Platform, providing a business data fabric that connects data, semantics, processes, and policies, while preserving business context that gives data meaning. The innovations announced this week extend these capabilities making enterprise data more accessible and providing agents with the trusted business context for successful AI.
Extend the business data fabric with an open lakehouse foundation
Enterprise data is distributed across sources, including databases, warehouses, and data lakes. Making that data accessible across environments often requires duplicating copies, increasing costs and making it harder to maintain consistent business context.
With the completed acquisition of Dremio, SAP is enhancing the open lakehouse foundation for business users and AI agents to access, share, and work with distributed data across the landscape.
- Discover, govern, and share data across platforms: SAP BDC now supports native Apache Iceberg and a universal catalog powered by Apache Polaris, providing an open and governed data foundation for users and Joule to consume data. Together with SAP BDC Connect, this builds on SAP’s commitment to platform interoperability with zero-copy data sharing across partners including Databricks, Snowflake, Google, AWS, and Microsoft.
- Query distributed data with zero copies: Supported by Dremio’s high-performance SQL query engine, users can federate access across lakehouses and relational databases including SQL Server, MongoDB, Oracle, and Postgres without moving data. Through integration with Joule Work, business users can ask complex questions in natural language and get answers grounded in trusted SAP and custom data products and the business context behind them, without needing to know where the data resides or how to query it.
- Accelerate analytics and AI autonomously: For developers, maintaining query performance requires building summary tables, updating materialized views, or creating separate BI extracts to keep analytical queries fast enough for analytics and AI. This engineering work is reduced with Dremio’s Reflection technology, which learns from how your data is being used and automatically precomputes and optimizes the results your workloads need. As workloads change, Reflections adapt with them, removing the need for manual performance tuning while delivering sub-second performance at scale for analyst queries and high-concurrency agentic workloads.
“With SAP Business Data Cloud, we are building an enterprise foundation that unifies, governs, and is ready for innovation, so analytics and AI can scale without compromising the quality, compliance, and trust.”
Ganesh Sivakumar, Global Chief Data Analytics & AI Officer, Mead Johnson Nutrition
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We also announced an expansion of the partnership with Databricks, bringing the latest set of industry-leading data platform capabilities including Lakeflow, Agent Bricks, Unity Gateway, and Lakebase to SAP Databricks in SAP Business Data Cloud.
SAP Application Data Foundation makes data from SAP applications available for consumption in your SAP BDC engine of choice, including SAP Databricks. This provides a cloud-native way to access data in SAP Business AI Platform, helping to lower the total cost of ownership and reduce time to value. SAP data products can subsequently be shared across the business data fabric using SAP BDC Connect for zero-copy access, avoiding the creation of additional pipelines, data copies, and silos.
For example, a manufacturer could use historical sales, inventory, and supply chain data to develop AI models for demand forecasting. The data is accessible from SAP BDC, where data professionals can enrich it with third-party data and create custom data products in SAP Databricks. Data engineers can build models on a semantically rich foundation, helping produce forecasts grounded in logic that is already embedded in SAP systems while accelerating model development.
Build a trusted system of context across domains
Unified master data is only as valuable as the governance applied to it. Across the enterprise, the same customer, supplier, or product can appear differently across systems with different identifiers, attributes, and relationships. For an AI agent, understanding that these records represent the same business entity is essential for making trusted decisions.
Earlier this year, we announced the acquisition of Reltio, adding capabilities to help customers cleanse, harmonize, and unify data across systems. With the acquisition now complete, SAP Reltio is now generally available in SAP BDC, bringing multi-domain master data management natively into the business data fabric.
SAP Reltio’s AI-based entity resolution matches and reconciles records across SAP and third-party systems to create unified, 360-degree views of business entities, including customers, suppliers, products, and other critical entities. By bringing together trusted attributed, relationships and business interactions SAP Reltio gives business users and agents a more complete understanding of these entities across sources. These trusted profiles can be made available as governed data products in SAP BDC, giving Joule and Joule agents consistent, connected business context to support decisions and actions.
Turn enterprise knowledge into reusable business context for AI
Every organization operates according to a defined set of business rules, relationships, processes, and policies that determine how decisions are made. SAP Knowledge Graph provides rich business context across your data, connecting thousands of entities, relationships, and rules, creating a comprehensive view of the enterprise. Agents working on specific tasks need access to the context most relevant to the business problem they are solving, rather than the full enterprise model.
At SAP TechEd Berlin, we introduced SAP Business Data Cloud Ontology Manager, a new AI-assisted experience that enables teams to create domain-specific views of SAP Knowledge Graph for applications, agents, or defined business scenarios. These curated views bring together the entities and relationships most relevant to each use case, grounding agents in the right business context they need to solve a particular business problem.
For example, a collections agent needs to understand customers, invoices, payment terms, and credit risk. SAP Business Data Cloud Ontology Manager lets teams create and publish a domain view for collections. This context helps Joule Agents connect information across these business entities, supporting answers and recommendations that reflect the relationships and rules relevant to the scenario. Because these views inherit definitions and governance from SAP Knowledge Graph, teams can reuse the same business semantics in views for related use cases, such as cash flow or order management, without having to redefine those concepts.
Get started
- Learn more about SAP Business Data Cloud
- Discover how business context connects AI, actions, and outcomes
- Getting started with SAP Business Data Cloud
Irfan Khan is president and chief product officer of SAP Data & Analytics.
