Author
Abstract
Data engineering and analytics have revolutionized the aviation industry through the transformation of vast operational datasets into actionable intelligence. Modern aircraft generate terabytes of information through thousands of onboard sensors, creating unprecedented opportunities for optimization across multiple domains. Despite technological advances, a significant portion of this valuable data remains underutilized due to fragmented systems and processing limitations. The implementation of advanced analytics frameworks has enabled proactive maintenance strategies, enhanced safety protocols, improved passenger experiences, and optimized air traffic management. Airlines leveraging these capabilities have achieved substantial improvements in resource utilization, operational reliability, safety metrics, and customer satisfaction while simultaneously reducing costs and environmental impact. The integration of distributed computing frameworks and machine learning algorithms has particularly accelerated this transformation, enabling real-time processing of high-velocity data streams and driving predictive capabilities that anticipate operational needs before they manifest. As aviation continues to evolve, the strategic deployment of data engineering capabilities will remain critical for competitive advantage and operational excellence in an industry characterized by complex interdependencies and thin profit margins.
Suggested Citation
Srinivasa Rao Kotla, 2025.
"Data Engineering and Analysis in Aviation: A Comprehensive Review,"
Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(5), pages 847-853, May.
Handle:
RePEc:alk:jcsts0:v:7:y:2025:i:5:id:9895
DOI: 10.32996/jcsts.2025.7.5.96
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