One reason for the popularity and the constant success of Cubeware Importer is its openness towards the various databases and pre-systems. This is based on the knowledge of the impossibility of a “eierlegende Wollmilchsau - jack of all trades device” or in other words, on the awareness that each database system has its individual strengths and weaknesses. The best possible use of the respective strengths by Cubeware Importer is the continuous challenge for Cubeware’s product developers.
Show Hierarchies as Dimensions...
This can be seen very strikingly in the current release 9.4, which provides significant innovations for handling the in-house CW1 database and IBM's Planning Analytics (TM1). A major advantage of CW1/TM1 is that data can be written directly into the OLAP cube/multidimensional database without detours via relational tables. This makes this database system particularly interesting for planning applications. However, what could not be done as elegantly as with other database systems so far was the handling of multiple parallel hierarchies. This led to the fact that in particular the dimensioning of the OLAP cubes became in a way more complex and time consuming. As a result, the desired performance could often not be achieved to the extent desired, depending on the application. Since IBM provided a REST API (application programming interface) for Planning Analytics 2.0 (still known under the old name "TM1"), it has been possible to overcome this shortcoming. With the new TM1R driver of the Importer for CW1/TM1, Cubeware has succeeded in doing just that. With Release 9.4 and the new driver included, it is possible for the first time to create OLAP cubes with multiple parallel hierarchies with the Importer CW1/TM1 and to evaluate them elegantly in the Cubeware frontends.
It goes on
Data sources are becoming more and more heterogeneous due to new technological possibilities and the technical concepts based on them, such as big data, advanced analytics, machine learning and artificial intelligence. The times when it was "enough" to load data from financial accounting into a business intelligence tool are finally over. For example, Advanced Analytics processes must be controlled (see also our white paper Advanced Analytics), different data sources must be connected, the data prepared and put into a meaningful context. This often means that hybrid database architectures are used that combine the respective strengths of the various databases so that applications can be created that allow users to access decision-relevant information quickly and easily via the Cubeware frontends, or to generate and visualize this information there.
In the beginning there was the Cubeware Importer, today it is the most sold Cubeware product and tomorrow it will be even more the central interface for controlling the data streams towards the users. With the innovations that Release 9.4 brings with it, he has gone a good deal further in this direction.