Modelling Dark Data Management Framework: a Grounded Theory

Abstract

The phenomenon of Big Data has no longer become a new issue for business players as the evolution of the big data characteristics from the classical 3Vs (volume, velocity, and variety) expanded to become the 42Vs. Interconnected electronic devices and IoT tremendously contribute to the increasing incidents of Big Data, which are not only experienced personally but also by businesses. While the awareness of dark data is still lacking and the evidence of publication merely exhibits an approach to the dark data phenomenon, this creates a huge gap in the subject matter clearly. Therefore, the study was proposed to investigate dark data management by Malaysian SMEs for business operations. The core of the study does not compensate the SMEs for the better way of managing dark data, but rather focuses on investigating its current circumstances. The study employed a qualitative approach to investigate the major purpose of the research and propose to analyze the data using Grounded Theory Methodology (GTM). As a result, the identification of the valuable dark data residing in the enterprise repository can be defined appropriately, providing insight on the construction of the management of dark data framework.