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.
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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), 311–326.
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