Exploring the Evolution of Big Data Technologies: A Systematic Literature Review of Trends, Challenges, and Future Directions
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| Yayımlandı: | Future Internet vol. 17, no. 9 (2025), p. 427-456 |
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| Yazar: | |
| Diğer Yazarlar: | , |
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MDPI AG
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| Online Erişim: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231464 |2 nlm | ||
| 100 | 1 | |a Hakami, Tahani Ali |u Department of Accounting and Finance, Jazan University, Jazan 82721, Saudi Arabia; thakami@jazanu.edu.sa | |
| 245 | 1 | |a Exploring the Evolution of Big Data Technologies: A Systematic Literature Review of Trends, Challenges, and Future Directions | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Literature Review | ||
| 520 | 3 | |a 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. | |
| 653 | |a Data management | ||
| 653 | |a Big Data | ||
| 653 | |a Velocity | ||
| 653 | |a Marketing | ||
| 653 | |a Data processing | ||
| 653 | |a Datasets | ||
| 653 | |a Bibliometrics | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Edge computing | ||
| 653 | |a Trends | ||
| 653 | |a Decision making | ||
| 653 | |a Privacy | ||
| 653 | |a Data analysis | ||
| 653 | |a Literature reviews | ||
| 653 | |a Batch processing | ||
| 653 | |a Ethics | ||
| 653 | |a Real time | ||
| 653 | |a Strategic planning | ||
| 700 | 1 | |a Alginahi, Yasser M |u Department of Computer Science, Adrian College, Adrian, MI 49221, USA; yalginahi@adrian.edu | |
| 700 | 1 | |a Sabri, Omar |u Zekelman School of Business & IT, St. Clair College, Windsor, ON N9A 6S4, Canada | |
| 773 | 0 | |t Future Internet |g vol. 17, no. 9 (2025), p. 427-456 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3254515446/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3254515446/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3254515446/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |