Exploring Big Data Applications for Knowledge Management in Higher Education Administration

Abstract

This paper presents a comprehensive investigation into the utilization of big data for enhancing knowledge
management processes within the management systems of higher education institutions. Amidst the burgeoning data
landscape, academic institutions confront the challenge of harnessing voluminous and multifaceted data streams to bolster
decision-making, curricular development, and strategic planning. Our research method encompasses a multi-case
study analysis of five large universities that have pioneered the incorporation of big data analytics into their operational
and academic knowledge frameworks. By conducting interviews with key stakeholders, including academic leaders, IT
specialists, and policymakers, and by scrutinizing existing data architectures, we aim to construct a detailed picture of the
current practices and potential growth areas in the field. The findings reveal that while some institutions have advanced
in specific domains of knowledge management, such as student performance tracking and resource allocation, there
remains significant untapped potential in areas like faculty collaboration networks and research output optimization. The
study identifies the critical barriers to effective big data utilization, which include legacy technology infrastructures, data
silos, and a skills gap among administrative staff. Conclusively, this paper argues that the strategic alignment of big data
initiatives with institutional knowledge objectives is paramount. We propose a framework for a systematic approach to big
data in higher education that encompasses governance, technological infrastructure, and a culture of data-informed decision-
making. This research contributes to the emergent discourse on data-driven transformation in educational settings,
offering actionable insights for institutions aspiring to navigate the complexities of the digital age.