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Exploring the Evolution of Big Data Technologies: A Systematic Literature Review of Trends, Challenges, and Future Directions

Author

Listed:
  • Tahani Ali Hakami

    (Department of Accounting and Finance, Jazan University, Jazan 82721, Saudi Arabia)

  • Yasser M. Alginahi

    (Department of Computer Science, Adrian College, Adrian, MI 49221, USA)

  • Omar Sabri

    (Zekelman School of Business & IT, St. Clair College, Windsor, ON N9A 6S4, Canada)

Abstract

This study examines the evolution and impact of Big Data technologies across sectors, emphasizing key algorithms, emerging trends, and organizational challenges in their adoption. Special attention is given to ethical concerns related to data privacy, security, and scalability, underscoring the importance of responsible governance frameworks. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to ensure transparency and methodological rigor. A comprehensive literature search identified 83 peer-reviewed articles from high-indexed journals, and a complementary bibliometric analysis of 1108 Scopus-sourced articles (2015–2024) was conducted using R Biblioshiny. This dual-method approach offers both qualitative depth and quantitative insights into major trends, influential sources, and leading countries in Big Data research. Key findings reveal that real-time data processing and AI integration have significantly enhanced data management capabilities, supporting faster and more informed organizational decision-making. This study concludes by highlighting the importance of ethical governance and recommending future research on sector-specific adoption patterns and strategic frameworks that maximize Big Data’s value while safeguarding privacy and trust.

Suggested Citation

  • Tahani Ali Hakami & Yasser M. Alginahi & Omar Sabri, 2025. "Exploring the Evolution of Big Data Technologies: A Systematic Literature Review of Trends, Challenges, and Future Directions," Future Internet, MDPI, vol. 17(9), pages 1-29, September.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:9:p:427-:d:1753829
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    References listed on IDEAS

    as
    1. Vangelis Marinakis & Themistoklis Koutsellis & Alexandros Nikas & Haris Doukas, 2021. "AI and Data Democratisation for Intelligent Energy Management," Energies, MDPI, vol. 14(14), pages 1-14, July.
    2. Kenneth David Strang & Zhaohao Sun, 2017. "Big Data Paradigm: What is the Status of Privacy and Security?," Annals of Data Science, Springer, vol. 4(1), pages 1-17, March.
    3. Chang, Victor, 2021. "An ethical framework for big data and smart cities," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    4. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    5. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    6. repec:plo:pone00:0241865 is not listed on IDEAS
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