Due to the significant growth in storage and processing capacities, considerably larger amounts of information in both the personal and professional environment can now be recorded and made available in the form of digital data. Examples of this include profiles or posts in social networks, purchase histories of individual customers in online stores as well as movement profiles or health records. Such data is often generated automatically and at a high level of granularity when using internet-based services such as the World Wide Web.
This situation has a considerable impact on all business functional areas of companies, such as marketing, human resources, finance, procurement, production and logistics, as well as on corresponding areas of public organizations. However, in order to make meaningful use of the constantly growing, enormous amounts of data, appropriate skills and tools for merging, evaluating and analyzing are indispensable. For this reason, business economists today are also expected to have advanced qualifications with regard to the handling and processing of such data within the framework of specific software packages for information analysis and decision support and the underlying concepts and methods.
These challenges of intelligent data analytics are the subject of “business analytics”, which combines expertise from the fields of business intelligence, business modeling, data analysis & data mining, business informatics & data science, statistics & econometrics as well as optimization & simulation and applies them using appropriate IT systems and IT tools. With regard to the type of data use, a distinction is made between descriptive analytics (in the sense of automatically finding correlations in large amounts of data, or: “What happened?”), predictive analytics (in the sense of automatically deriving forecasts, or: “What will happen?”) and prescriptive analytics (in the sense of automatically deriving recommendations for action, or “What should happen - and what needs to be done to make it happen?”). Only the methodical development of holistic approaches that integrate techniques from all three areas enables the targeted support of business planning and decision-making processes as well as the intelligent digitalization of existing business processes.