The Data Management Platform of the Future?

Efficient access to business-relevant information is a key success factor in many companies today. Employees must be able to identify the relevant content quickly and in a targeted manner, even in extensive databases. This requires modern solutions that are not only scalable, but also react intelligently to the respective usage context.

This is precisely where SAP Datasphere comes in. The platform sees itself as an open data ecosystem with the aim of making information easily accessible and usable throughout the entire company - regardless of department or role.

SAP Datasphere harmonizes the requirements of the business departments for independent data work with the IT requirements for data control and security. This creates a central basis for future-oriented data management.

What sets Datasphere apart? 

Data lake house and classic DWH: Classic data warehouse solutions are increasingly reaching their limits when it comes to meeting modern business and technological requirements. The data lake house principle offers a much more flexible and scalable approach here. It combines the advantages of data lakes and data warehouses in a common architecture and enables both structured and unstructured data to be processed in a central location. SAP Datasphere picks up on this concept and creates the basis for smooth data integration - even across hybrid and cloud-based infrastructures.

Flexible interfaces

A key strength of SAP Datasphere is its high level of integration capability with a wide range of technologies. In cooperation with renowned partners such as Google Cloud, Databricks, Collibra, Confluent and DataRobot, an open data ecosystem is being created that significantly simplifies the management, protection and connection of complex data landscapes. Companies not only benefit from better use of their existing systems, but can also develop innovative data-based applications more easily.

What functions does SAP Data-sphere provide? The functions of Datasphere cover the following areas in particular:

Data provision: SAP Datasphere always provides data from SAP systems in the appropriate business context. Semantic information and links that have already been defined in the SAP applications can be transferred automatically. This makes it easier to map even very complex data models and significantly reduces manual effort. At the same time, end-to-end governance along the entire data lifecycle ensures that data integrity and security are guaranteed at all times.

Data enrichment: SAP Datasphere makes it possible to merge different data sources and map them in a common semantic model. In this way, even complex data landscapes can be standardized and efficiently made available for use in the company. The integrated SAP Datasphere Marketplace can also be used to supplement your own data projects with external, industry-specific data sets. At the same time, it is possible to make self-developed data products available to others and actively market them.

Standardization of the data landscape: SAP Datasphere gives companies centralized access to data, regardless of whether it is in the cloud or in a hybrid environment. Controlled self-service for specialist departments can be set up via Spaces. At the same time, existing content from SAP BW can be integrated and reused via the BW Bridge. This saves time, reduces the migration effort and enables the efficient use of existing data models.

Business Data Fabric: SAP Datasphere helps companies to manage complex and growing data landscapes more easily. It connects data sources and AI platforms in a shared environment and enables access to information in real time. This accelerates business processes and creates a business data fabric that creates an end-to-end, consistent database.

With this holistic approach, SAP Datasphere offers a powerful foundation for companies that want to make their data infrastructure fit for the future and meet the increasing demands for integration, scalability and efficiency.

Example from practice

When a company processes an order, the associated data is not usually stored in a single table. Instead, information such as currency, access rights or security rules are distributed across several tables that are related to each other. If such a dataset is transferred from one system to another, this functional relationship is often lost. This not only makes data maintenance more difficult, but also control over authorizations and data flows.

What if this context could be preserved? What if the relationships between tables remained recognizable, access rights were clearly traceable and at the same time it was visible where the data is located and how it is linked to each other? This is exactly what would make the creation and operation of central data platforms such as data warehouses much more efficient and transparent.

With the increasing use of cloud technologies, this challenge has become even more complex. Companies that work with multiple source systems and integrate both local and cloud-based data sources across different providers need to keep a particularly careful overview of their data contexts.

SAP Datasphere offers a completely new approach here. The platform provides a central semantic layer and a uniform catalog structure with which the business context of the data can be permanently mapped. On this basis, companies can build a so-called business data fabric architecture in which data is not used and managed in isolation, but with its respective meaning and logic.

Datasphere - for whom? 

Datasphere is aimed at companies that want to consolidate their data landscape and use advanced analysis and AI functions at the same time. These can be integrated either directly via the SAP Hana Cloud or by connecting partner solutions such as Databricks. 

Such technologies are crucial for gaining usable insights from constantly growing volumes of data that support strategic decisions and contribute to value creation. SAP Data-sphere is therefore aimed at organizations of all sizes that want to modernize their database and make it fit for the requirements of digital business models.

Conclusion

SAP Datasphere stands for modern and holistic data management that significantly simplifies the handling of distributed data sources. The platform makes it possible to provide information from different systems in a standardized, technically meaningful context. This creates a flexible and scalable environment that can cope with both current requirements and future developments.

Thanks to the integration of the latest technologies and cooperation with leading partners, SAP Datasphere offers companies a future-proof basis for the sustainable further development of their data strategy

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