SAP Datasphere in Business Data Cloud

Simplify your data landscape with access to trusted, context-rich business data across SAP and third-party systems.
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What is SAP Datasphere?

SAP Datasphere is a key component in SAP Business Data Cloud, serving as the knowledge core that unifies semantics, data products, and modeling to preserve business context across hybrid and multi-cloud environments.

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Turn data into shared business understanding that powers analytics, applications, and AI by:

  • Connecting SAP and third-party data sources across an open data ecosystem.

  • Preserving business context with shared semantics and metadata.

  • Delivering governed data with business-ready data products.

  • Modeling and harmonizing enterprise data for reuse across domains.

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Bridge the gap between data strategy and AI agents

Watch The Fabric of Data & AI event replay to learn how Google, Ericsson, and Vodafone connect business context to data for trusted AI at scale.

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Key benefits

Preserve business context across all your data

Maintain universal business context across data, processes, and policies so outcomes are optimized and reflect how your business operates.

Simplify your data landscape

Unify SAP and third-party data in a single, governed foundation to reduce duplication and enable access across hybrid and multi-cloud environments.

Deliver trusted, AI-ready data

Apply shared semantics and reusable data models to deliver consistent, trusted data that accelerates insights and enables context-aware decisions across analytics and AI.

Key features

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Unified data integration across every pattern

Connect data sources using the right pattern, including batch, streaming, replication, or data federation, while preserving business semantics across hybrid and cloud environments.

Analytical and semantic modeling

Build multi-dimensional views of data with analytic models that define measures, hierarchies, and semantics, ensuring consistent structure and understanding across workloads.

Knowledge graph for connected context

Map relationships across data and business processes to surface meaningful patterns and provide the trusted context AI agents need to act with confidence.

Data product creation and sharing

Explore SAP-managed data products in the Catalog, build custom ones using SAP Business Data Cloud, or enrich data with external industry sources via the Data Marketplace.

Governed, self-service data access

Organize and govern data with secure, virtualized spaces that enable controlled ownership and data product sharing across domains.

Zero-copy data sharing across platforms

Connect SAP and third-party data and metadata across environments with bidirectional, zero-copy data sharing through an open data ecosystem.

Reduce TCO and accelerate AI with a business data fabric

Learn how a unified business data fabric lowers total cost of ownership and accelerates trusted AI compared to DIY approaches in this GigaOm report.

Read the report

See how customers are succeeding with SAP

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Hershey: Gaining deeper insights into how to keep the future prosperous and sweet with SAP solutions

See how The Hershey Company is modernizing its approach to data to gain insights that will keep the future tasting sweet.

Alcon: Extracting and analyzing data from billions of records in the blink of an eye

Read how SAP Datasphere and SAP Analytics Cloud help eye-care company Alcon visualize and analyze vast amounts of data from multiple sources in real time. Learn how its improved decision-making allows the company to meet customer needs and patient demands effectively and swiftly.

CAF: Connecting data and platforms with SAP Business Data Cloud to drive innovation and smarter mobility

Find out how Construcciones y Auxiliar de Ferrocarriles, S.A. (CAF) connects data to fuel digital innovation. CAF is a global leader in transportation systems and mobility. With the SAP Business Data Cloud solution, CAF is connecting third-party solutions, improving data insight, and revolutionizing efficiency.

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How ZEISS uses SAP solutions to improve decision-making and data accessibility

See how ZEISS, an internationally leading technology enterprise in optics and optoelectronics, is enhancing its analytical capabilities with real-time data extraction using SAP HANA Cloud and SAP Datasphere, with ambitions to improve data integration by using SAP Business Data Cloud.

Take an interactive product tour

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Explore how you can use SAP Datasphere to model data, build data products, and apply business semantics to deliver context-rich data for analytics and AI.

Resources

Explore expert insights and practical guidance on building a business data fabric and activating context-rich data for AI.

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Evolve your SAP BW environment

Modernize at your own pace with the new SAP Business Data Cloud capabilities, our open partner ecosystem, and proven migration tools.

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BDC Catalog in SAP Discovery Center

Explore SAP Business Data Cloud capacity services with missions, roadmaps, and guidance to help you connect, manage, and analyze SAP and third-party data.

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Getting started series: Experience SAP Business Data Cloud

Learn how to use SAP Business Data Cloud to turn raw data into real-time insights with prebuilt apps, data modeling tools, and SAP Databricks.

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The fabric of data and AI

Learn how SAP Business Data Cloud brings together context, governance, and orchestration to accelerate insights and intelligence.

FAQ

SAP Datasphere is a key component of SAP Business Data Cloud, providing data integration, semantic modeling, and data product capabilities that contribute to the unified knowledge core and serve as a foundation for its business data fabric architecture.

A business data fabric is an architecture that connects data, semantics, and business processes into a unified layer, enabling access to context-rich data across systems without duplication. This foundation supports reliable, scalable AI by ensuring models and agents operate with consistent business context rather than fragmented or isolated data signals.

SAP Datasphere provides a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data product management, discovery and activation, and virtualization. It enables data professionals to distribute mission-critical business data with business context and logic preserved across the data landscape.

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