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Big Data at the Service of Universities: Towards a Change in the Organizational Structure and the Decision-Making Processes

  • Dina SidaniEmail author
  • May Sayegh
Chapter
Part of the Lecture Notes in Information Systems and Organisation book series (LNISO, volume 30)

Abstract

If the information is at the heart of economic intelligence and institutional power, the data are the essential elements to build knowledge for a decision making that might seem to be optimal in view of the opportunities and knowledge available at a given time. Today, with the explosion of mass data which are characterized by their diversity, their nature and their connections to other objects, Business Intelligence shows its limits. In a context where business competitiveness depends on the use of technology for processing the data to facilitate decision making, Big Data seems to be the right solution. Nowadays, the variety of data sources and the need for fast and real-time processing demand new methods of data storage and analysis. Big Data is a (R) evolution of technologies and decision-support approaches. It precisely allows refining the understanding of the situation and improving decision efficiency through prediction. The adoption of Big Data has profound implications in institutions. It is the organizational structure that is called into question, calling not only for new decision-making approaches but also and especially for new profiles. In the same context, there is a growing interest among institutions of higher education in taking advantage of Big Data to improve student performance, while reducing administrative work load. Higher educational institutions can benchmark their student, professor and curriculum performance against like universities, offering yet new insight into the potential for improvement. Through a qualitative study conducted in 6 universities, we will show how the adoption of Big Data will transform the organizational structure and the decision-making processes within the universities of Lebanon.

Keywords

Big data Data analysis Structural (R) evolution Organizational structure Decision-making processes Data scientist University perspectives 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of ManagementSaint-Joseph UniversityBeirutLebanon

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