Data has been the backbone of innovation for decades. And in today’s AI-powered economy, their role is more important than ever. Today, data must be provided in such a way that both humans and AI agents can understand it and take appropriate action without hesitation.

At SAP, we believe in providing an ecosystem that simplifies your data landscape and preserves the business-critical context of all your data. This is made possible by a business data fabric.

This architectural approach is the result of decades of evolution – from cubes to warehouses to lakehouses – that now culminates in a data fabric architecture that brings together the true meaning of data to enable AI projects to succeed at scale.

Simplify data landscapes – with a data fabric architecture

Earlier this year, we announced SAP Business Data Cloud, making end-to-end business data fabric capabilities available to anyone who relies on business-critical SAP data, including fully managed SAP Databricks.

This week at SAP TechEd we presented the SAP Snowflake solution extension for SAP Business Data Cloud. This means that Snowflake’s data and AI functions are directly available to SAP customers.

Together with SAP Business Data Cloud, this offers companies the flexibility to choose the right computing power and storage options for all data and AI workloads. This extends your business data fabric while ensuring governance, interoperability and semantics. SAP Snowflake will be available as a solution extension directly through SAP, providing customers with a simplified operational experience.

For many customers, integrating data across multi-cloud and hybrid environments adds complexity, especially when merging transactional and analytics workloads. Too often, this process creates a hidden burden on data by losing the business context and semantics that give data its meaning.

We recently announced SAP BDC Connect, a feature that allows customers to bi-directionally exchange data and metadata in SAP Business Data Cloud with their existing Databricks and Google Cloud environments without copying. Today we are excited to introduce SAP BDC Connect for Snowflake. This makes it much easier for customers to harmonize and manage business-critical data, regardless of where it is stored.

Linking all data

As companies simplify their data landscapes, building a trustworthy data foundation that is anchored in the business context is a top priority. A global survey of 1,200 leading companies, including technology companiesfound that nearly half are investing more in harmonizing business data, underscoring the growing importance of leveraging data based on industry standards.

To accelerate this progress, SAP provides fully managed data products as a core component of SAP Business Data Cloud, now with innovations for deeper coverage and expanded connectivity:

• Data Product Studio: A new feature in SAP Business Data Cloud to create, model and manage reusable data products with visual tools and SQL-based transformations from a single workspace. Users can define schema, lineage, and logic to bring SAP and other data together into managed resources with full version control and lifecycle management. This is an easier way to share data products across all business units and ensure consistent definition of data across the data fabric architecture.
• Additional SAP data products: About SAP Business Data Cloud are now new data products available, including SAP Cloud ERP and SAP SuccessFactors or sustainability and customer experience products. This enables even broader coverage across all business areas.

• Bidirectional data exchange: It is now possible to share data between SAP Business Data Cloud and SAP HANA Cloud, unlocking the value of data for both transactional and analytical workloads. Customers can reuse existing objects such as SAP HANA calculation views directly in SAP Business Data Cloud, preserving business logic and KPIs and ensuring governance as they extend models across their data fabric architecture.

Extend agents and applications with an AI database

We’re expanding SAP HANA Cloud with new features that take it to a new level as an AI database for building agents and intelligent applications. It allows developers to connect and understand all types of data, be it structured or spatial data, graphs or vector embeddings, all in a single in-memory engine.

Today we’re expanding these multi-model capabilities with three key innovations that make it easier to build agent-based AI experiences.

• Advanced knowledge graph capabilities that enable precise agents: With SAP HANA Cloud’s knowledge graph engine, customers can now automatically generate knowledge graphs from SAP HANA cloud metadata. The automatically created graph contains tables and columns and can show data relationships. These knowledge graphs are customizable and combinable, allowing developers to examine data mappings, change graph structure, perform semantic searches, and use them to provide agents with the business context they need to draw accurate conclusions.
• Model Context Protocol (MCP) support for HANA Cloud: We are expanding SAP HANA Cloud and now support the Model Context Protocol (MCP). This allows Joule Agents to access the comprehensive multi-model engines of SAP HANA Cloud. While SQL remains the standard for databases, support for MCP enables Joule Agents to go beyond rows and columns to find touchpoints with unstructured data and understand relationships, locations and meanings across all data types. In practice, this means that Joule Agents can navigate relationships between customers and suppliers, analyze geographic dependencies using spatial data, and perform semantic searches via vector embeddings.

• Tabular AI features: With this integration with SAP AI Core, you can run AI workloads such as forecasting, anomaly detection, and predictive models directly based on structured business data from SAP HANA Cloud. In addition to ready-to-use tabular AI models, customers also get access to SAP RPT-1, a new transformer-based base model. This model is natively embedded in SAP HANA Cloud and provides forecasts without prior task-specific training. Developers can use simple SQL procedures to bring AI closer to their SAP data and generate semantically comprehensive results.

A data fabric architecture provides a deeply integrated ecosystem for all company data. With SAP Business Data Cloud and SAP HANA Cloud, a fully managed solution is also available for all data and AI workloads, ensuring that business context is maintained across the entire data landscape.