The purpose of cross-system analytics is to consolidate, transform and clean data from source systems and thereby provide a central and consistent view for reporting and analyzing data within an organization.
When data is exchanged among several source systems, it is very likely that the data does not fit together from a business or technical context. When the data is exchanged, functionality is needed to bring the different data sets together to create one common data foundation (i.e. core data model).
Very often a core data model is defined numerous times for different purposes. In many cases, this is because minor metadata must be added. For example technology solutions for integration, user interface, analytics or transactions unnecessarily require their own data models. This increases the total cost of ownership (TCO) as the same content must be provided several times. Due to the incompatible meta-models, cross topics like user interface integration, extensibility or authorization, must be solved various times. This results in high TCO and encounters consumption of solutions by customers.
In case of cross-system analytics, application data from one or more source systems is replicated into separate database schemas in a target system, one schema for each source system. Local views may be defined on top of those external application database tables. Local views of different source systems may be combined into cross views for implementation of cross-system analytics scenarios
Although there may be cross-system analytics scenarios where the number of the involved systems of same type is already known during design time (e.g. exactly one SAP enterprise resource planning (ERP) system and one SAP customer relationship management (CRM) system are relevant), other scenarios exist where the role of the involved systems is known in advance (e.g. SAP ERP) but not the number of each type of system. This may be because the number of systems of a particular system type may depend on the explicit customer system landscapes (e.g. n×SAP ERP). However this information is necessary for the definition of cross CDS views in order to provide cross-system scenarios that must be applicable for different customer environments without the knowledge of explicit customer system landscapes.
Different options exist to master the challenge of not having any knowledge about the explicit customer system landscape while still needing to define cross views. For cross-system scenarios, respective cross views could be defined and subsequently extended by customer to their specific system landscapes. However, the extensibility concept of an involved database environment is not powerful enough to allow enhancements of cross views by customers or partners. Customers could also copy or modify delivered cross views, however the customer would then be cut off from bug-fixes or new releases of the views delivered by the service provider.
Therefore, the inventors perceive a need to develop a solution for defining cross views when the system landscape is not known without sacrificing any of the flexibility of having a virtual data model.