SAP Datasphere

In a nutshell

SAP Datasphere is SAP's modern data management and data modeling platform. It enables the integration, modeling, and delivery of data from SAP and non-SAP systems for analytics, planning, and AI applications.

Within the SAP portfolio, Datasphere serves as the semantic data layer. It ensures that data is described in business terms, harmonized, and made available as reusable data products for various use cases. In the context of the SAP Business Data Cloud, Datasphere is a central component of the future SAP data architecture.

Why is SAP Datasphere important?

Many companies today have a data landscape that has evolved over time. Data is scattered across SAP ERP, SAP S/4HANA, SAP BW, CRM systems, cloud applications, and other platforms. At the same time, demands for reporting, planning, self-service analytics, and AI are on the rise.

In the past, such requirements were often addressed through complex data warehouse environments or numerous individual interfaces. This led to redundant data sets, inconsistent definitions of key performance indicators, and high maintenance costs.

SAP Datasphere takes a different approach. The platform provides a common semantic layer on which business data can be described in domain-specific terms and made available to different user groups. This enables data to be used more consistently and made available more easily for analytics, planning, and AI.

Datasphere is particularly relevant in the context of SAP’s current data strategy. SAP positions the platform as a central modeling and integration layer within the SAP Business Data Cloud. While SAP Databricks serves as the pro-code platform for data engineering and AI, Datasphere acts as the business and semantic layer for reusable data products.

For many SAP customers, this raises the question of what role SAP BW, Datasphere, Databricks, and the SAP Business Data Cloud should play in their target architecture. This is precisely where Datasphere becomes a strategic issue.

‍How does celver AG provide support?

celver AG helps companies develop modern data architectures based on SAP and non-SAP technologies. In doing so, we do not view Datasphere in isolation, but always in the context of the overall target architecture.

A common mistake many companies make is to view Datasphere as the successor to SAP BW. In practice, however, the issues at hand are usually much more fundamental: What data platform will be needed in the future? What role do data products play? When does Databricks make sense? How can analytics, planning, and AI be supported together?

celver AG supports customers in:

Development of a Data Strategy
Datasphere's Position Within the SAP Roadmap
Development of Data Products
Integration of SAP and Non-SAP Data
Integrating Datasphere and Databricks
Modernization of Existing BW Environments
Building Modern Analytics and Planning Architectures

The focus here is not on the technology itself, but rather on the question of which architecture will best support corporate management, analytics, and future AI applications in the long term.

Related Terms

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SAP Business Data Cloud

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Databricks

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SAP BW/4HANA

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SAP Analytics Cloud (SAC)

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Data Product

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Data Fabric

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Data Mesh

Frequently Asked Questions

Is SAP Datasphere the successor to SAP BW?

Not exactly. While SAP does offer migration paths for existing BW environments, Datasphere serves a different purpose and is part of a more comprehensive data architecture. In the future, many companies will operate hybrid environments in which BW, Datasphere, and other platforms are used in parallel.

What is the difference between SAP Datasphere and SAP Databricks?

Datasphere focuses on domain modeling, semantics, and the delivery of data products. SAP Databricks, on the other hand, addresses data engineering, machine learning, and AI applications. Both platforms complement each other within the SAP Business Data Cloud.

Do I need Datasphere if I'm already using Databricks?

That depends on the target architecture. Many companies combine both technologies. While Databricks supports technical data processing and AI, Datasphere provides the business and semantic view of the data.

What role does Datasphere play in AI?

AI requires consistent and technically meaningful data. Datasphere supports the harmonization, description, and provision of this data, thereby creating an important foundation for analytics and AI applications.

What are data products in SAP Datasphere?

Data products are technically defined, reusable datasets that can be used for analytics, planning, or AI. Datasphere provides the semantic foundation for their modeling and delivery.

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