The success of companies depends on their ability to quickly and comprehensively gain insights from data and generate added business value. In this way, companies create a reliable basis for business decisions. In the past, the data warehouse has been an important core element in business intelligence architectures and has acted as the central basis for integrating data.
One weakness of the classic data warehouse approach is its lack of flexibility when it comes to building new data models or adapting existing data models to changing business processes. Without corresponding self-service options for the business department, these tasks lie exclusively with IT, which thus often becomes a bottleneck and takes a very long time to process. In many cases, this constellation leads to the business departments setting up their own shadow IT in order to model, as it were, bypassing IT.
In the face of increasing requirements, companies are being challenged to redesign their data warehouse strategy and adapt it to the changing environment. Companies have multi-cloud landscapes and significantly more complex IT architectures than in the past. Whereas previously 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 challenge is to bring together the data from a multitude of systems – and not only by IT. Ideally, the business departments should also be able to do this. It is equally important to connect and integrate SAP and non-SAP systems, either on-premise or provided from the cloud, in order to make data-based decisions. Data should be accessed in real time, if possible.
To become truly data-driven organizations, companies face the task of driving the shift from traditional data warehousing to a more comprehensive data management approach. Data management is about bringing order and structure to the multitude of data and data models, as well as making them appropriately available to consumers. This also includes the exchange of data models between departments. Only by linking data and business context can the maximum benefit be extracted from the available data so that it becomes the basis for successful decisions.
SAP Datasphere supports companies in the concept of data management. Its functionalities cover many requirements that companies have in this area. With a large number of connectors ready out-of-the-box, SAP Datasphere offers extensive connectivity options. Connectivity in turn forms the prerequisite for the topics of data federation and data integration. SAP Datasphere also meets these requirements. It offers virtual, direct access to the data without having to replicate it. This guarantees short processing times and ensures that users can use the data in near real time. At the same time, flexibility in the direction of data integration is maintained, for example, if a lot of logic is required for data processing or direct access is not an option for performance reasons. The existing data model does not have to be explicitly adapted for this purpose.
In addition, there are other aspects with which SAP Datasphere contributes to the data management approach. The business layer enables the business department to model business scenarios without knowing the underlying data models. It thus takes into account the increasing demands of the business department in terms of self-services. The business catalog comprises a central metadata repository with descriptions of the existing data models, key figures and information used in the company.
The previous approach of moving data from sources into a central data warehouse is no longer appropriate. In the future, it is not data that should be brought to technology, but technology to data. At the same time, the business context is retained, which enables the business departments to act more independently and flexibly. While IT can focus on processing data and maintaining data integrity, business units are able to link data, turn it into insights, and share the results of their analysis immediately – without delays, manual processes, or data duplication. Data management also means bringing IT and business users closer together. SAP Datasphere creates greater harmony between business needs and technical imperatives.