ISSN: 2222-6990
Open access
Qualitative research using 18 case studies were conducted as it allows in-depth investigation and to derive as rich evidence as possible from the selected cases. The data were collected using semi-structured interview on Malaysian Small and Medium Enterprises (SMEs) and the interviews were recorded and transcribed. The transcribed data were analyzed using Grounded Theory Methodology to identify emerging theory on dark data. The purpose of the paper is to investigate the dark data phenomenon towards Small & Medium Enterprise in Malaysia in relation to the scenario of dark data as experienced by SME in Malaysia in relation to its handling consequences towards business entity. The research findings elucidate how Malaysian SMEs dealt with the dark data phenomenon's occurrences which outlined the new model of Dark Data Lifecycle Management. There is a dearth of literature in the area on dealing with dark data, which demonstrates that dark data epistemology is still emerging. Thus, based on the experiences of Malaysian SMEs, a theory was modelled to demystify the dark data lifecycle management.
Ahmed, W., & Ameen, K. (2017). Defining big data and measuring its associated trends in the field of information and library management. Library Hi Tech News. 9, 21-24.
Baragan, S. P. (2020). Appraisal and retention of information in the private sector: a case study.(Doctoral Dissertation). Retrieved from
https://eprints.qut.edu.au/199783/1/Salvador_Barragan_Thesis.pdf
Birks, M., & Mills, J. (2014). Grounded theory: A practical guide. 2nd Edition. Los Angeles, CA: Sage.
BNM. (2013). Circular on New Definition of Small and Medium Enterprises (SMEs). Retrieved on 2nd July 2021 from
https://www.bnm.gov.my/documents/20124/761700/Appendix1-Circular_on_Definitions+_for_SMEs.pdf
Charmaz, K. (2008). Constructing Grounded Theory. 2nd Edition. Sage Publications: London.
Commvault (2014). 5 Ways to Illuminate your dark data. US: Commvault Systems.
Corallo, A., Crespino A. M., Vecchio, V. D., Lazoi, M., & Marra, M. (2021). Understanding and Defining Dark Data for the Manufacturing Industry. IEEE Transactions on Engineering Management,
Delve. (2010). The Essential Guide to Coding Qualitative Data. Retrieved 2021 June 21st from https://delvetool.com/guide
Dimitrov, W., Siarova, S., & Petkova, L. (2018). Types of dark data and hidden cybersecurity risks. DOI: 10.13140/RG.2.2.31695.43681
Erik, J. M. (2016). Dark Data: Analyzing Unused and Ignored Information. econtentMag.com
Gharehchopogh, F. S., & Khalifelu, Z. A. (2011). Analysis and evaluation of unstructured data: text mining versus natural language processing. 2011 5th International Conference on Application of Information and Communication Technologies (AICT), 1-4.
Gimpel, G. (2020). Dark data: the invisible resource that can drive performance now. Journal of Business Strategy
Gimpel, G., & Alter, A. (2021). Benefit From the Internet of Things Right Now by Accessing Dark Data. IT Professional. 23(2), 45-49.
Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory. Strategies for Qualitative Research. Chicago: Aldine
Glass, R., & Callahan, S. (2014). The Big Data-driven business: how to use big data to win customers, beat competitors, and boost profits. Berlin: Wiley.
Guetat, S., & Dakhli, S. (2015). The Architecture Facet of Information Governance: The Case of Urbanized Information Systems?. Procedia Computer Science, 64, 1088-1098.
Hand, D. J. (2020). Dark Data: Why What You Don't Know Matters. USA: Princeton University Press.
Hitachi. (2013). Big Data - Shining the light on enterprise dark data (EDD). Retrieved April 15, 2019 from https://www.hitachivantara.com/en-us/resources.html
Highquest Solution. (2016). Dark Data Making your Organisation data-enabled? Retrieved on April 4th, 2019 from https://doczz.net/doc/8987800/white-paper-dark-data-making-your-organisation-data
IBM. (2013). The fundamentals of data lifecycle management in the era of big data : How data lifecycle management complements a big data strategy. Retrieved on June 25, 2021 from http://hosteddocs.ittoolbox.com/TheFundimentals.PDF
Intel. (2018). Datumize and Intel transform dark data into operational insight for manufacturing and logistics. Accessed: May 31, 2019. [Online]. Available: https:// www.intel.sg/ content/ dam/ www/ public/ us/ en/documents/solution-briefs/datumize-dark-data-in-manufacturing- and- logistics- solution- brief.pdf
Kantardzic, M. (2020). Data Mining: Concepts, Models, Methods, and Algorithms. Wiley: New Jersey.
Kumar, K., & Banyal R. K. (2020). Data Life Cycle Management in Big Data Analytics. Procedia Computer Science. 173, 364–371.
Mayer-Sch¨onberger, V., & Cukier, K. (2013). Big data: a revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt.
Miller, K., Miller, M., Moran, M., & Dai B. (2018). Data Management Life Cycle: Final Report. Texas, Texas A&M Transportation Institute.
Schembera, B., & Duran, J. M. (2020). Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer. Philosophy & Technology. 33, 93–115
Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Thousand Oaks, CA: Sage
Urquhart, C. (2013). Grounded Theory for Qualitative Research: A Practical Guide. Sage Publications: London.
In-Text Citation: (Ajis et al., 2022)
To Cite this Article: Ajis, A. F. M., Zakaria, S., & Ahmad, A. R. (2022). Modelling Dark Data Lifecycle Management: A Malaysian Big Data Experience. International Journal of Academic Research in Business and Social Sciences, 12(3), 328–344.
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