Challenges of Implementing Big Data Technology in Higher Institutions
Abstract
The aim of this study is to investigate the challenges of implementing Big Data Technology (BDT) in Higher Educational Institutions (HEIs) in Namibia. The study further undertook quantitative surveys with staff of the three (3) higher institutions in Namibia. A sample of 345 participants from International University of Management (IUM), Namibia University of Science and Technology (NUST), and The University of Namibia comprising the study's population (UNAM) were selected for this study using the simple random sampling technique. The data collected was analysed for descriptive statistics using the Statistical Package for Social Sciences (SPSS). The finding indicated that there are challenges such as lack of awareness of BDT, lack of support for management and inadequate IT infrastructure. The study further recommended strategy that will enhance the implementation of BDT in HEIs.
Downloads
References
[2] B. Alsheikh, A Noura, “Developing an Integrated Framework to Utilize Big Data for Higher Education Institutions in Saudi Arabia”. International Journal of Computer Science & Information Technology (IJCSIT). 8, 89–96, 2019.
[3] A. Banik, & S. K. Bandyopadhyay, “Big Data- A Review on Analysing 3Vs”. Journal of Scientific and Engineering Research, 2(1),2016,
[4] N. Baker., & N. Baker, “How Can Higher Education Benefit from Big Data?” QS. https://www.qs.com/how-can-higher-education-benefit-from-big-data/, 2017.
[5] M. Bamiah, & S. Brohi & R. Bashari, Big data technology in education: Advantages, implementations, and challenges. Journal of Engineering Science and Technology, 2018.
[6] B. K. Daniel, & R. Butson, “Technology enhanced analytics (TEA) in higher education”, Proceedings of the International Conference on Educational Technologies, 29 November–1 December, 2013, Kuala Lumpur, Malaysia, and pp. 89–96, 2013.
[7] B. Daniel, Big Data and analytics in higher education: Opportunities and challenges. British Journal of Educational Technology, 2015.
[8] M. J. Mazzei, Big Data and Strategy: Theoretical Foundations and New Opportunities. Intech Open. https://www.intechopen.com/books/strategy-and behaviors-in-the-digital-economy/big-data-and-strategy-theoretical-foundations-and new-opportunities, 2019.
[9] A. McAfee, E and E. Brynjolfsson, “Big Data. The Management Revolution”. Harvard Business Review, 90(10), pp. 60–9, 2012.
[10] J. Murumba , & E. Micheni, (2017). “Big Data Analytics in Higher Education: A Review”. The International Journal of Engineering and Science. 06. 14-21. 10.9790/1813 0606021421, 2017.
[11] M.H Padgavankar and S. R. Gupta, Big Data Storage and Challenges. International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2014, 22182223, 2014.
[12] J. O. Osakwe, N. Dlodlo & N. Jere, “Learners’ perception on mobile learning towards the adoption of mobile learning in Namibian High schools. A case of the Otjozonjupa region”. Proceedings of IST Africa conference, Windhoek. May, 2017.
[13] J. O Osakwe, N. Dlodlo, N. Jere, “A Proposed Framework for the Adoption of Mobile Learning in Namibian High Schools”. Journal of Educational Policy and Entrepreneurial Research ISSN: 2408 -770X (Print), ISSN: 2408-6231 (Online)Vol. 4, N0.2. 2017. Pp 104-124, 2017.
[14] S. Pawar, “A Study on Big Data Security and Data Storage Infrastructure”. International Journal of Advanced Research in Computer Science and Software Engineering. 6. 539-542, 2016.
[15] A. G. Picciano, “The evolution of big data and learning analytics in American higher education”. Journal of Asynchronous Learning Networks, 16 (3), 9-20, 2012,
[16] F. Provost, and T. Fawcett, “Data Science and its Relationship to Big Data and Data Driven Decision Making”. Big Data, 1(1), pp. 51–59, 2013,
[17] A. Rabella & Marc-Fuster , “OECD Centre for Educational Research and Innovation”. Nov 07, 2016
[18] B. Schmarzo, “Big Data. Understanding how data powers big businesses”. Wiley 2013.
[19] A. Sin and L. Muthu, “Application of big data in education data mining and learning analytics – a literature review”. Faculty of Education and Languages, Open University Malaysia, Malaysia. ICTACT Journal on soft computing: special issue on soft computing models for big data, July 2015, volume: 05, issue: 04


- I certify that I have read, understand and agreed to the Journal of Information Systems and Informatics (Journal-ISI) submission guidelines, policies and submission declaration. Submission already using the provided template.
- I certify that all authors have approved the publication of this and there is no conflict of interest.
- I confirm that the manuscript is the authors' original work and the manuscript has not received prior publication and is not under consideration for publication elsewhere and has not been previously published.
- I confirm that all authors listed on the title page have contributed significantly to the work, have read the manuscript, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission.
- I confirm that the paper now submitted is not copied or plagiarized version of some other published work.
- I declare that I shall not submit the paper for publication in any other Journal or Magazine till the decision is made by journal editors.
- If the paper is finally accepted by the journal for publication, I confirm that I will either publish the paper immediately or withdraw it according to withdrawal policies
- I Agree that the paper published by this journal, I transfer copyright or assign exclusive rights to the publisher (including commercial rights)