Business Data Fabric: Providing data with business context

When companies succeed in quickly and comprehensively gaining insights from data and generating business value, they create a reliable basis for business decisions. However, the effective provision and use of data presents many companies with immense challenges.

How to move from SAP BW to SAP Datasphere

Distributed data landscapes as a challenge

Today’s enterprise reality is multi-cloud landscapes and significantly more complex IT architectures than in the past. Whereas in earlier times data from the ERP system was mainly used for analytics, reporting and planning, today the relevant information is highly distributed in different systems at various providers and hyperscalers.

The task for companies is to bring their data sources together and make reliable decisions based on data-driven insights. To better exploit the potential of data, a reorientation of the data architecture from the classic data warehouse approach to a data mesh concept implemented in the form of a business data fabric is conducive.

Decentralized architecture with data mesh and data fabric

Data mesh refers to a decentralized approach to sharing, using and managing data. It shifts responsibility for data to the business departments. The concept promises to solve some of the most pressing challenges companies face in designing and using their data landscape, and paves the way to a domain-driven data architecture. In the data mesh, each business department is responsible for the definition, quality and creation of data from its own domain.

Similar to the data mesh, the data fabric is a novel approach to data architecture that allows data to be seamlessly integrated and leveraged across multiple systems, applications, and platforms. The data fabric provides a unified view of enterprise data and empowers organizations to efficiently use, analyze, and derive valuable insights from their data. From an organizational perspective, the data fabric concept is the ideal infrastructure to streamline processes across the enterprise.

Maintaining the business logic of the data

The business data fabric goes one step further than the traditional data fabric approach. Not only does it simplify complex data landscapes and deliver meaningful data to all data users, but it also retains the business logic and application context of the data. So with a business data fabric, there is no need to recreate all the business context that is lost when data is extracted and replicated. As a result, stakeholders and data consumers can make informed decisions very quickly and confidently because the data is always completely available to them – regardless of where it is stored.

With SAP Datasphere to the business data fabric

SAP Datasphere forms an essential technological basis for establishing a decentralized data architecture in the company. The successor product to SAP Data Warehouse Cloud is a unified solution for data integration, data cataloging, semantic modeling, data warehousing, data federation and data virtualization.

With its diverse functionalities, SAP Datasphere offers companies the possibility to collect, process and integrate data from various sources. It does not matter whether the data is structured or unstructured and whether it comes from SAP or non-SAP systems. SAP Datasphere uses advanced analytics tools and machine learning algorithms to transform data into actionable insights that serve as the basis for business decisions.

The entire setup is an ideal fit with our holistic approach to the Business Analytics Platform (BAP). This not only focuses on technology, but also takes into account relevant framework parameters such as organization, employees, data governance, and so on. The Business Analytics Platform thus forms a reliable basis for data-based decisions.

Conclusion: How to convert data into insights

Data mesh principles are becoming increasingly important to the future of data management. Likewise, flexible business data fabric architectures are gaining massive importance. Because of the features available, SAP Datasphere is ideal for implementing a decentralized data organization. For example, it is possible to use spaces to organize data in such a way that departments can manage their data themselves. The graphical data modeling is state of the art and an explicit business layer provides additional flexibility for the creation and adaptation of data models.

In short, SAP Datasphere enables business users to quickly turn data into insight and action – a key competitive advantage for continued growth and profitability.