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Impact Of Big Data On Business Intelligence And Decision Support Systems

Author

Listed:
  • Mohammad Rashid SAADAT

    (MATE-Hungarian University of Agriculture and Life Sciences, Gödöllő, Hungary)

  • Patrick SIEGFRIED

    (International Management Department, ISM International School of Management, Mörfelder Landstraße 55, 60598 Frankfurt/Main, Germany, https://orcid.org/0000-0001-6783-4518)

Abstract

Big Data is now poised to mutate decision-making systems. Indeed, the decision is no longer based solely on the structured information that was hitherto collected and stored by the organization, but also on all data not structured outside the corporate straitjacket. The cloud and the information it contains impacts decisions and the industry is witnessing the emergence of business intelligence 3.0. With the growth of the internet, social networks, connected objects and communication information are now more abundant than ever before, along with rapid and substantial growth in their production. In 2012, 2.5 exabytes of data (one exabyte representing a million gigabytes of data) came every day to swell the ranks of big data (McAfee et al., 2012), which should weigh more than 40 zettabytes from 2020 (Valduriez, 2014) for 30 billion connected devices (The Internet Of Nothings, 2014) and 50 billion sensors (Davenport & Soulard, 2014). One of the most critical aspects of all of this information flow is the impact these will have on the way decisions are made. Indeed, in the part of an environment in which data was scarce and difficult to obtain, it was logical to let decision-making be conditioned by the intuition of the experienced decision-maker (Klein, Phillips, Rall, & Peluso, 2007). However, since information and knowledge are now available to everyone, the role of experts and decision-makers is gradually changing. Big data, in particular, makes it possible for analytical and decision-making systems to base their decision-making on global models. However, considering all the dimensions of the situations encountered, it was not until now that these systems were not within the reach of man, but were rationally limited (Simon & Newell, 1971). Big data and however, the processing of unstructured data requires modifying the architecture of decision support systems (DSS) of organizations. This paper is an inventory of developments undergone by aid systems decision-making, under the pressure of big data. Finally, it opens the debate on ethical questions raised by these new technologies, and it is observed that now, data analysis of personal data has become more debatable than in the past.

Suggested Citation

  • Mohammad Rashid SAADAT & Patrick SIEGFRIED, 2021. "Impact Of Big Data On Business Intelligence And Decision Support Systems," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 18, pages 145-152, December.
  • Handle: RePEc:cmj:networ:y:2021:i:18:p:145-152
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    Cited by:

    1. Fabian SCHMIDTKE & Patrick SIEGFRIED, 2022. "Implementation Strategies Of A Modern Showroom Concept For Retailers With A Wide Range Of Products," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(1), pages 7-22, May.

    More about this item

    Keywords

    Intuition; Decision; Decision Support Systems; Rationality; Business Intelligence;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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