Optimizing Airline Efficiency Using Big Data and Predictive Analytics

Year : 2026 | Volume : 13 | 01 | Page :
    By

    Tamasa Priyadarsini,

  • Achinta Kumar Palit,

  • Preetiprada Samantara,

  1. Assistant Professor, Dept. of CSE, GIET Ghangapatana, Bhubaneswar, Odisha, India
  2. Assistant Professor, Dept. of CSE, GIET Ghangapatana, Bhubaneswar, Odisha, India
  3. Student, Dept. of CSE, GIET Ghangapatana, Bhubaneswar, Odisha, India

Abstract

Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within the airline industry. A structured search was carried out across major scholarly databases—including Web of Science, ScienceDirect, Google Scholar, and IEEE Xplore—using relevant keywords associated with big data analytics, data mining, predictive analysis, and machine learning. The reviews show that Big Data Analytics (BDA) is commonly applied in airline operations, optimizations, customer service, risk management, safety and aircraft maintenance. The review further reveals that the adoption of Big Data Analytics (BDA) in the airline industry is constrained by challenges such as data integration complexities, strict regulatory compliances requirements, data privacy and security concerns. In summary, this study presents a comprehensive review of current Big Data Analytics (BDA) applications in the airline sector while highlighting key implementation challenges. These insights enrich the existing literature and serve as a useful foundation for the future research as well as practical applications of data – driven solutions in airline operations.

Keywords: Big Data Analytics (BDA), airlines industry, data mining, predictive analytics and machine learning

How to cite this article:
Tamasa Priyadarsini, Achinta Kumar Palit, Preetiprada Samantara. Optimizing Airline Efficiency Using Big Data and Predictive Analytics. Journal of Advanced Database Management & Systems. 2026; 13(01):-.
How to cite this URL:
Tamasa Priyadarsini, Achinta Kumar Palit, Preetiprada Samantara. Optimizing Airline Efficiency Using Big Data and Predictive Analytics. Journal of Advanced Database Management & Systems. 2026; 13(01):-. Available from: https://journals.stmjournals.com/joadms/article=2026/view=242261


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Ahead of Print Subscription Review Article
Volume 13
01
Received 27/01/2026
Accepted 01/02/2026
Published 20/03/2026
Publication Time 52 Days
36

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