ILLUMINATING DARK DATA:

A SYSTEMATIC LITERATURE REVIEW OF ITS CHARACTERISTICS AND MANAGEMENT STRATEGIES

Abstract

The phenomenon of dark data refers to information that organizations collect but fail to utilize effectively, often due to its unstructured nature. This article conducts a systematic literature review (SLR) to define dark data comprehensively and explore its characteristics and management strategies. Despite the growing recognition of dark data's potential value, a formal definition remains elusive, with various scholars offering differing perspectives. The review synthesizes findings from 182 articles, ultimately narrowing down to 81 relevant publications that highlight the challenges of categorizing and accessing dark data. Key characteristics identified include unused, ignored, and unmeasured data, which often reside in an organization’s repositories without being analyzed or exploited. The study also discusses the implications of dark data on compliance, cybersecurity risks, and organizational efficiency. By addressing the gaps in existing literature, this research aims to establish a clearer understanding of dark data and propose frameworks for effective management. The insights gained from this review are particularly relevant for small and medium enterprises (SMEs) in Malaysia, providing a foundation for future research and practical applications in optimizing data utilization while mitigating associated risks. Ultimately, this work underscores the necessity of recognizing and managing dark data as a critical component of modern data governance strategies.