Knowledge management is more concerning on reflection and analysis than regarding architectures and taxonomies, as much regarding connecting people as gathering content, and more concerning on building communities than building databases. As knowledge is majorly kept in heads instead of hard disks, it is a lot tougher to manage than information. However, knowledge management must be developed on a foundation of excellent information management and data management. This paper aims to investigate the factors of big data analytics in enabling the knowledge management practice. Four major factors discovered are the storage factor, processing factor, security factor and quality factor. The theoretical framework is proposed for the future research on examining the significant relationship between the factors of big data analytics and the knowledge management.
Adrian, C., Abdullah, R., Atan, R., & Jusoh, Y. Y. (2017). Factors influencing to the implementation success of big data analytics: A systematic literature review. 2017 International Conference on Research and Innovation in Information Systems (ICRIIS), 1–6. https://doi.org/10.1109/ICRIIS.2017.8002536
Ardagna, C. A., Ceravolo, P., & Damiani, E. (2016). Big data analytics as-a-service: Issues and challenges, 3638-3644.
Cai, L. & Zhu, Y. (2015). The challenges of data quality and data quality assessment in the big data era. Data Sci. J., 14(2), 1-10.
Cárdenas, A. A., Manadhata, P. K., & Rajan, S. P. (2013). Big data analytics for security. IEEE Security & Privacy,74-76.
Chauhan, S., Agarwal, N., & Kar, A. K. (2016). Addressing big data challenges in smart cities: a systematic literature review. https://doi.org/10.1108/info-03-2016-0012
Delhi, N. (2016). Quality issues with big data analytics, 3589-3591.
Eckhoff, D. & Sommer, C. (2014). Driving for big data? Privacy concerns in vehicular networking. IEEE Security Privacy, 12(1), 77-79.
Halaweh, M., & Massry, A. E. (2015). Conceptual model for successful implementation of big data in organizations. J. Int. Technol. Inf. Manag., 24(2), 21-29.
Harris, I., Wang, Y. and Wang, H. (2015). ICT in multimodal transport and technological trends: Unleashing potential for the future. International Journal of Production Economics, 159, 88-103.
Hou, C.-K. (2013). Measuring the impacts of the integrating information systems on decision-making performance and organisational performance: An empirical study of the Taiwan semiconductor industry. Int. J. Technol. Policy Manag., 13(1), 34-66.
Jadon, K. S., & Bhadoria, R. S. (2015). 2015 International conference on Computational Intelligence and Communication Networks A review on costing issues in big data analytics, 727-730. https://doi.org/10.1109/CICN.2015.148
Jayasingh, B. B., Patra, M. R., & Mahesh, D. B. (2016). Security issues and challenges of big data analytics, 204-208.
Kache, F., Seuring, S., Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of big data analytics and supply chain management. https://doi.org/10.1108/IJOPM-02-2015-0078
Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013). Big data: Issues and challenges moving forward, 995-1004. https://doi.org/10.1109/HICSS.2013.645
Katal, A. (2013). Big data: Issues, challenges, tools and good practices, 404-409.
Khan, M. A., Uddin, M. F., & Gupta, N. (2014). Seven V ’s of big data understanding big data to extract value.
Kim, M.-K. & Park, J.-H. (2016). Identifying and prioritizing critical factors for promoting the implementation and usage of big data in healthcare. Inf. Dev., 1-13.
Koronios, A., Gao, J., & Selle, S. (2014). Big data project success - A meta analysis. in 18th Pacific Asia Conference on Information Systems, PACIS, p. 376.
Liu, C., Wang, J. S., Lin, C., Liu, C., Wang, J. S., & Lin, C. (2017). The concepts of big data applied in personal knowledge management. https://doi.org/10.1108/JKM-07-2015-0298
Lu, R., Zhu, H., Liu, X., Liu, J. K., & Shao, J. (2014). Toward ef?cient and privacy-preserving computing in big data era. IEEE Network, 28(4), 46-50.
Lugmayr, A., Stockleben, B., Scheib, C., Mailaparampil, M. A., Lugmayr, A., Stockleben, B., … Mailaparampil, M. A. (2017). Cognitive big data: Survey and review on big data research and its implications. What is really “new” in big data? https://doi.org/10.1108/JKM-07-2016-0307
Nambiar, R., Bharadwaj, R., Sethi, A., & Vargheese, R. (2013). A look at challenge and opportunities in big data analytics in health care. IEEE International Conference in Big Data, 17-22.
Pauleen, D. J., Wang, W. Y. C., Pauleen, D. J., & Wang, W. Y. C. (2017). Does big data mean big knowledge? KM perspectives on big data and analytics. https://doi.org/10.1108/JKM-08-2016-0339
Rothberg, H. N., Erickson, G. S., Rothberg, H. N., & Erickson, G. S. (2017). Big data systems: Knowledge transfer or intelligence insights? https://doi.org/10.1108/JKM-07-2015-0300
Sumbal, M. S., Tsui, E., See-to, E. W. K., Sumbal, M. S., Tsui, E., & See-to, E. W. K. (2017). Interrelationship between big data and knowledge management: An exploratory study in the oil and gas sector. https://doi.org/10.1108/JKM-07-2016-0262
Tallon, P. P. (2013). Corporate governance of big data: perspectives on value, risk, and cost. IEEE Computer Society.
Wang, Y. & Hajli, N. (2017). Exploring the path to big data analytics success in healthcare. J. Bus. Res., 70, 287-299.
Rafhi, N. A. M., & Rahman, S. A. (2017). Factors of Big Data Analytics in Enabling the Knowledge Management Practice. International Journal of Academic Research in Business and Social Sciences, 7(11), 840-849.
Copyright: © 2018 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode
