DEMYSTIFYING DARK DATA CHARACTERISTICS IN SMALL AND MEDIUM ENTERPRISES: A MALAYSIAN EXPERIENCE

• Published in: Journal of Theoretical and Applied Information Technology
• Main Author: Ajis A.F.M.; Zakaria S.; Ahmad A.R.
• Format: Article
• Language: English
• Published: Little Lion Scientific 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127483981&partnerID=40&md5=5b59af6104175e314a89bedc19c672d9

The paper reports a study on the dark data phenomenon experienced by Small & Medium Enterprise in Malaysia in relation to characteristics of dark data from SME perspectives. Qualitative research was conducted upon 13 cases which derived from the Inductive Grounded & Emergent Theory Sampling, implemented to identify appropriate samples for the study. Data was collected using semi-structured interviews which were recorded, transcribed, and analyzed using the Grounded Theory Methodology. The research findings highlighted the characteristics and types of dark data typically resides in SME repositories. The study further shows that the field is lacking in literature on dealing with dark data which depicts dark data epistemology are still evolving. Thus, based on Malaysian SMEs' experience a theory was suggested to demystify dark data management. © 2022 Little Lion Scientific. All rights reserved.