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SAP Datasphere
Unleash the Potential of Your Data in the
SAP Business Data Cloud (BDC)
Roland J. Merz
Managing Director / Vice Chairman
Take Your Data to the Next Level – with SAP Datasphere
The SAP Datasphere serves as the central data management and integration solution of the SAP Business Data Cloud, providing companies with simple and efficient access to their data.
Through the seamless integration of data from SAP and third-party systems, SAP Datasphere creates a unified view of business information, promotes data-driven decisions through real-time analytics, and accelerates the adoption of Business Intelligence, AI, and Data Science solutions.
It thus forms the core of the SAP Business Data Cloud.
Basic Concept
As part of the Data Fabric approach, SAP Datasphere forms the technical foundation for a centralized and integrated data architecture. It unifies data from different sources, manages it automatically, and provides it consistently. With a scalable, secure data infrastructure, you simplify governance processes and avoid manual reconciliations through centrally integrated, consistent data.
At the same time, SAP Datasphere also offers the possibility of a decentralized architecture in the context of a Data Mesh, where each team or department is responsible for managing the data it generates or requires. Teams or departments are empowered to work independently while ensuring high data quality and security. The Space Concept forms the technical foundation of the Data Mesh in SAP Datasphere. At the same time, there remains room for central control by an existing analytics or BI organization.
A complete implementation of the Data Mesh principle is possible, but not mandatory.
Data Integration and Modeling
With SAP Datasphere, you can quickly and easily connect, harmonize, and prepare your data from a wide variety of source systems for analysis. Through a user-friendly web interface, SAP Datasphere allows you to connect to your systems with just a few clicks. The list of supported connectors already includes many common providers and is continuously being expanded. Data integration can be performed virtually or via replication, depending on your requirements.
You can build your data models using low-code/no-code with just a few clicks, but you can also leverage SQL to handle more complex scenarios with ease. For example, you are free to create data joins via drag & drop or by using SQL. Additionally, Python is available as a versatile programming language to integrate custom scripts or complex transformations directly into your data processes.
To enable the use of further complex programming languages, seamless integration with SAP Databricks is also available.
SAP Datasphere supports all types of data – whether structured, semi-structured, or unstructured. The platform offers a high degree of flexibility to work effectively with different data formats. Data Lakes or Data Lake Files extend SAP Datasphere with a storage solution for large and diverse data volumes from SAP and non-SAP sources. Through SAP Datasphere, these raw data can be modeled, transformed, and made usable for analytics and AI applications. For data analysis, SAP Datasphere can be connected with your familiar analytics tools, such as SAP Analytics Cloud (SAC), Microsoft Excel (via SAC), and 3rd-party tools (via OData or JDBC/ODBC).
Space Concept and Data Products
Spaces represent separate work areas.
They enable a decentralized organization of data and the resulting data products. This allows business units to work independently (and without relying on IT).
This is managed through dedicated user and access rights. By assigning individual resources to each space, they can be efficiently distributed.
In this way, SAP Datasphere enables a scalable, collaborative data organization.
Cataloging and Semantic Modeling
Create a central catalog for both your data and the data products of external providers. This catalog is available to all (authorized) users and can be searched with ease.
In addition, SAP Datasphere allows the creation of comprehensive documentation.
Semantic modeling enables you to build models from a business perspective. This allows you to create an entity-relationship model and also define key figures, hierarchies, dimensions, and relationships that match your business processes.
KI & Databricks
The integration of Databricks into the SAP Business Data Cloud creates a seamless way to leverage data engineering, advanced analytics, AI, and machine learning. The use of historical data for making accurate predictions, the automation of complex analysis processes, and the optimization of business operations are just some of the advantages that Databricks provides. The insights gained can in turn be brought back into SAP Datasphere and used, for example, for operational evaluations.
The use of SAP Business AI within the SAP Business Data Cloud gives you access to Joule AI Copilot and Joule AI Agents. Thanks to the Joule AI Copilot, you get a chatbot that, based on your data and questions, can provide interesting and previously unknown insights. Of course, it adheres to ethical and data protection standards!
With the help of the AI Agents, you can automate and optimize your processes. To this end, SAP offers department-specific solutions in the form of data products.
From SAP BW to SAP Datasphere with the Data Product Generator
The development of SAP’s data warehouse solutions reflects the shift from classic, centralized data architectures to open, flexible cloud approaches. SAP Datasphere goes far beyond the traditional functions of SAP BW: instead of a centralized, heavily IT-driven data warehouse, it offers an open, cloud-based platform that seamlessly integrates structured and unstructured data from SAP and non-SAP systems.
To ease the transition from a classic SAP BW system to SAP Datasphere, SAP provides several options. One of these is the SAP BW Data Product Generator. With the SAP BW Data Product Generator, you can transfer data that no longer changes from SAP BW on HANA or BW/4HANA (Private Cloud Edition) into SAP Datasphere and reuse it there as data products. If you want to migrate an actively used SAP BW data flow into SAP Datasphere, the SAP BW Data Product Generator can support you by creating persistence objects and loading historical data. (Further information from SAP)
Data Governance
With SAP Datasphere, data access can be managed with precision. Who is allowed to access which data is defined through roles and permissions at the space and object level.
Automatic data lineage (Data Lineage) makes it possible to fully trace objects and data models. Through the integrated Data Marketplace, both internal and external data products can be provided, shared, and consumed.
The Data Marketplace promotes enterprise-wide data collaboration, supports the creation of a trusted data network, and lays the foundation for data-driven decisions without losing sight of governance and security.
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