Harnessing and Mitigating Big Data Governance Challenges Using Hybrid Approach: A Systematic Literature Review

Abstract

The advent of big data has brought about significant opportunities and valuable insights to modern organizations. However, the proliferation of governance challenges is increasing dramatically, which necessitates searching for innovative approaches for managing, securing, and complying with government and organizational policies. This study conducted a systematic literature review and explored the profound impact of big data governance on modern organizations and highlighted the existing prevalent challenges and evaluated the mitigation approaches. We obtained the results of our defined research questions from peer-reviewed articles, industry reports, and academic theses published between (2019-2024). The results of our findings are categorized into four fundamental components of big data governance (i.e., people, process, data, technology), through illustrative tables and figures. Furthermore, this study has identified the need for effective and adaptive frameworks and models that can respond to emerging technologies and big data governance practices. After identifying the existing approaches for harnessing and mitigating the existing big data governance challenges, this study has proposed a new hybrid approach that integrates the viable system model and big data governance process model. The proposed approaches not only mitigate the existing challenges, but also serves as a diagnostic tool for identifying the maturity level of data governance and pinpoint the areas for improvement. However, the practical implementation of the proposed approaches remains a limitation of this study, urging avenues for future studies to explore its applicability and impact on modern organizations.

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