Innovation and Big Data
Innovation is an essential issue for companies and educational institutes. We have seen that well-known companies came into trouble since they did not innovate in time. They kept their well-established way of operating and adhered to their old-fashioned business models. The main topic of this contribution is to address the question: to what extent can the availability of Big Data support the innovation attempts of companies and educational institutes?
We start by mentioning five examples of innovation and relate them to data science and big data. We describe basic concepts and developments. We then formulate six possible classes of obstacles and take into account the use of sensitive data. Finally, we arrive at two conclusions and three recommendations.
KeywordsBig data Obstacles Sensitive data Safeguards Turn around management Narrative science
This insight overview is the result of my cooperation with many colleagues. The following colleagues are singled out for their contribution to this article. I would like to thank Rob van Eijk, Daniel Dimov, Joost Kok, Aske Plaat, and Joke Hellemons. Moreover, I am grateful to Wladyslaw Homenda from Vilnius for the stimulating discussions we have had and for the invitation to communicate on Innovation.
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