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

Dina Sidani () and May Sayegh ()
Additional contact information
Dina Sidani: Saint-Joseph University
May Sayegh: Saint-Joseph University

A chapter in ICT for a Better Life and a Better World, 2019, pp 299-312 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-10737-6_19

Ordering information: This item can be ordered from
http://www.springer.com/9783030107376

DOI: 10.1007/978-3-030-10737-6_19

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().