AI in Optimizing Big Data Pipelines and Storage Systems

Authors

  • Naveena Kumari Nandale Vadlamudi

Keywords:

Artificial Intelligence Optimization, Big Data Pipelines, Intelligent Storage Management, Reinforcement Learning Scheduling, Explainable AI Governance

Abstract

Data center infrastructure faces escalating complexity as global data volumes grow exponentially,rendering rule-based management insufficient for modern enterprise platforms. This article presents the Governance-Aware AI Optimization Framework (GAAOF), an integrated architecture unifying pipeline orchestration, anomaly detection, storage optimization, and explainable governance for enterprise big data systems.

References

David Reinsel et al., "The Digitization of the World From Edge to Core," Seagate, 2018. [Online].

Available: https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage

whitepaper.pdf

Michael Armbrust et al., "A View of Cloud Computing," Communications of the ACM, 2010.

[Online]. Available: https://dl.acm.org/doi/10.1145/1721654.1721672

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Published

2026-04-28

How to Cite

Naveena Kumari Nandale Vadlamudi. (2026). AI in Optimizing Big Data Pipelines and Storage Systems . Journal of Computational Analysis and Applications (JoCAAA), 35(1), 1209–1228. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5391

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Section

Articles