Data are a major competitive factor. Big Data presents new challenges in terms of volume, speed and heterogeneity. The management of Big Data drives the entire data value chain. Our research model, BDMcube, visualizes the path taken by data from its raw state to its value-creating application. The key factor in the economic use of data analysis is its alignment with a targeted business effect. This involves interaction between the relevant data, the users and the organization, as well as computers and production machines. To establish an optimized decision-supporting database, data is analyzed for the purpose of recognizing patterns and structures. This is done by integrating existing data sources or generating new data. In the case of Big Data, cluster-based parallel processes are used to cope with the volume and speed of the data; also, schematic freedom in database systems helps to facilitate diversity. Blockchain systems are ideal for securing cross-business data exchange. The integration of existing data sources is expanded and valorized by generating new digital data using sensors and input devices.
The data intelligence research team develops methods and systems for the management and analysis of Big Data and develops software prototypes, and evaluates them on partners’ premises under real world conditions. The findings allow the artefacts to be improved and new products and processes developed for research and business partners.
