The evolution of business analytics : based on case study research
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- Master Thesis 
While business analytics is becoming more significant and widely used by companies from increasing industries, for many the concept remains a complex illusion. The field of business analytics is considerably generic and fragmented, leaving managers confused and ultimately inhibited to make valuable decisions. This paper presents an evolutionary depiction of business analytics, using real-world case studies to illustrate a distinct overview that describes where the phenomenon was derived from, where it currently stands, and where it is heading towards. This paper provides eight case studies, representing three different eras: yesterday (1950s to 1990s), today (2000s to 2020s), and tomorrow (2030s to 2050s). Through cross-case analysis we have identified concluding patterns that lay as foundation for the discussion on future development within business analytics. We argue based on our findings that automatization of business processes will most likely continue to increase. AI is expanding in numerous areas, each specializing in a complex task, previously reserved by professionals. However, patterns show that new occupations linked to artificial intelligence will most probably be created. For the training of intelligent systems, data will most likely be requested more than ever. The increasing data will likely cause complications in current data infrastructures, causing the need for stronger networks and systems. The systems will need to process, store, and manage the great amount of various data types in real-time, while maintaining high security. Furthermore, data privacy concerns have become more significant in recent years, although, the case study research indicates that it has not limited corporations access to data. On the contrary, corporations, people, and devices will most likely become even more connected than ever before.