In 2025, SAP restructured its data and analytics portfolio, positioning the SAP Business Data Cloud (BDC) as the new data foundation. Along with developments in business AI, this restructuring established the company’s strategic direction.
The focus for 2026 is on practical application. Following a period of architectural planning and product announcements,customers are now starting to test the Business Data Cloud and its related components in their own projects – where features are available. These initial projects will be the true test. They will reveal which use cases are mature enough for production, what can be implemented immediately, and which scenarios should start as a proof of concept.
I will examine the developments in three key areas:
- The Business Data Cloud, including its components for seamless planning, Datasphere, and tighter integration with SAP BTP.
- SAP’s evolving AI strategy, covering Joule Studio, the Agent Builder, and the new knowledge graph engine in SAP HANA Cloud.
- BI and analytics, where BusinessObjects BI 2025 continues to be part of a hybrid analytics stack.
How far along is SAP Business Data Cloud in becoming a data and analytics backbone?
In early 2025, SAP introduced the Business Data Cloud (BDC) as a foundational element of its future data and analytics architecture. The platform is designed to unify data from different source systems and make it available for analysis through a shared semantic layer. Because many SAP customers operate in heterogeneous system landscapes, SAP is also working toward a more open and collaborative data ecosystem with BDC.
A key technical feature of this strategy is zero-copy sharing, delivered through the new BDC Connect technology. With this method, data remains in its original source system but can be published to external platforms for bidirectional use without being physically replicated. This approach represents a shift away from a physically centralized data model. Instead, SAP centralizes semantics. The goal is to reduce redundant data copies, which should create long-term cost and integration benefits for customers.
SAP is also expanding its partnerships with major data platform providers. BDC Connect for Databricks has been available since October 2025. Integrations for Google BigQuery and Snowflake are scheduled for the first half of 2026, with Microsoft Fabric planned for the third quarter. These integrations aim to minimize data movement and should enable consistent analytics execution across different platforms.
In addition to data management, the BDC includes a front-end component. The SAP Analytics Cloud (SAC), the company’s strategic platform for CPM, BI, and analytics, is now integrated into the BDC offering. Although SAC currently maintains its own data storage, it is gradually shifting to BDC storage options, particularly the Datasphere component. The goals are to reduce redundant data storage, leverage the platform’s compute power for intensive planning scenarios, and deliver acceptable performance for business users.
One significant development is Seamless Planning, which has been generally available since the first quarter of 2025. With this architecture, SAP Analytics Cloud uses SAP Datasphere as the storage layer for planning data. This approach integrates data persistence and planning logic more tightly, while SAP Analytics Cloud remains the front end for modeling, simulation, and visualization. An update at the end of 2025 also allowed customers to use Datasphere facts directly in planning models – another step towards integration.
The Business Data Cloud is also designed to facilitate the transition for existing SAP BW and SAP BW/4HANA customers. The goal is to gradually migrate on-premises environments to the cloud and then manage their ongoing development within the BDC as part of a broader modernization strategy.
One component for this migration is the BW Data Product Generator, available since early 2025. This tool migrates classic BW models into the BDC environment, transforming SAP BW and SAP BW/4HANA platforms into a modern data product architecture while preserving existing business logic. The goal is a technology-driven migration path that reduces complexity and protect existing investments.
The Data Product Studio differs from this. SAP is positioning it as the primary tool for creating and managing data products directly within the BDC. General availability of the Studio is planned for the first half of 2026, and it will be central to operationalizing SAP’s data product approach.
Finally, SAP is advancing the integration between the SAP Business Technology Platform (BTP) and the Business Data Cloud. Initial SAP Build integrations enable organizations to embed data products directly into applications or use them in automation and extension scenarios. This integration confirms that the BDC is designed as a central foundation for data-driven business processes across the SAP ecosystem, not as an isolated platform. Through this approach, SAP is creating its “data and analytics backbone”: the platform layer that should support and connect all future innovations in data, analytics, and AI.
The integration between BTP and BDC is important for both data management and SAP’s business AI strategy. Previously, the technology foundation for SAP’s AI initiatives was based on BTP. The BDC now provides the necessary data, semantics, and business context. The knowledge graph in SAP HANA Cloud adds another technical base component to this architecture. The challenge for SAP is to integrate these components into a cohesive platform for data, semantics, and AI.
SAP’s business AI strategy: Core technology or ecosystem integration?
SAP is expanding its business AI platform with Joule Studio, generally available since the second quarter of 2025, and the built-in Agent Builder, which became available in the fourth quarter of 2025.
Joule Studio is a low-code/no-code capability within SAP Build that should enable companies to create company-specific Joule agents and skills. These agents are intended to access data from the Business Data Cloud and the knowledge graph to add semantic context to business scenarios.
The integrated Agent Builder adds a developer-focused layer to this architecture. It sould allow developers to build more complex, context-aware agents that can plan multi-step processes and execute actions across both SAP and non-SAP systems. Through this combination, SAP aims to bridge the gap between visual modeling and deep technical control. That is an ambitious goal.
For 2026, SAP has announced additional capabilities, including system-triggered agents, agent-to-agent (A2A) communication, and an option to add custom pre-processing and post-processing logic to existing Joule agents.
The knowledge graph on SAP HANA Cloud is another important component for these agents. The graph provides the foundation for semantic and knowledge-based data models. The long-term goal is for the graph to connect data, context, and machine intelligence, enriching both the BDC and BTP with a semantic layer. SAP’s vision for an end-to-end architecture that integrates the knowledge graph, BDC, and BTP is still under development. Successfully executing this vision will be critical to SAP’s position in the AI and data markets.
Knowledge graph technology is a foundational component of the modern AI landscape. SAP is also developing other in-house technologies, including a foundation model for tabular data, a prompt optimizer on BTP, and AI services that go beyond its traditional focus on “business AI.” This strategy signals a clear intent to build proprietary core AI competencies, not just to adopt existing technologies.
This raises a strategic question: Will SAP create more value through its own AI research, or by integrating more deeply with established AI ecosystems?
Developing proprietary foundation models and expanding semantic technologies shows ambition. However, this approach carries the risk of spreading resources too thin and failing to keep pace with the broader AI market. SAP must balance its strength in business software with the openness and speed that modern AI innovation requires.
The role of BusinessObjects BI 2025 in SAP’s analytics strategy
Amid the focus on the BDC, SAP also released the SAP BusinessObjects BI 2025 Edition. The suite has a long history of strategic and technical evolution. Today, its role in SAP’s portfolio is clearly defined: SAP Analytics Cloud is the strategic front end for planning and analytics, particularly since its integration into the Business Data Cloud offering.
Contrary to expectations, BusinessObjects remains part of SAP’s analytics portfolio, with development continuing at a measured pace. SAP has focused its efforts on a few core components, providing ongoing technical and functional enhancements. The current release prioritizes Web Intelligence (WebI), which now includes an offline mode. SAP has also extended maintenance through the end of 2027 and plans the next major release for the same year. This gives existing customers more time and planning certainty for modernizing their analytics landscapes.
Which roadmap promises are becoming production-ready solutions?
Following SAP’s architectural reorganization in 2025, the focus in 2026 shifts to real-world testing. These projects will determine whether the announced technologies perform as expected. The coming months will reveal which Business Data Cloud scenarios are ready for production and how the platform’s technical openness works in practice.
The AI landscape also remains highly dynamic. Key questions for the year ahead include the extent of SAP’s investment in proprietary foundational technologies, where the greatest business value will emerge, and adoption rates for these new capabilities.
