Integrating Artificial Intelligence–Enabled Analytics into Mission-Critical Data Platforms: An Architectural Framework

Authors

  • Ajay Srinivas Kiran Gemidi

Keywords:

Artificial Intelligence–Enabled Analytics, Mission-Critical Data Platforms, Data Architecture, Governance, Performance Isolation, Reliability, Workload Management

Abstract

Mission-critical data platforms increasingly incorporate artificial intelligence (AI) analytics to enablepredictive insights and data-driven decision making. However, AI workloads introduce variability inresource consumption, execution patterns, and governance requirements that can compromise the deterministic behavior expected from mission-critical systems

References

Nasir Abdul Jalil et al., "Machine Learning Trends, Perspectives and Prospects in Education Sector," Proceedings of the 3rd International Conference on Education and Multimedia Technology (July 2019) DOI:https://doi.org/10.1145/3345120.3345147 [Online]. Available: https://dl.acm.org/doi/pdf/10.1145/3345120.3345147

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Published

2026-04-02

How to Cite

Ajay Srinivas Kiran Gemidi. (2026). Integrating Artificial Intelligence–Enabled Analytics into Mission-Critical Data Platforms: An Architectural Framework. Journal of Computational Analysis and Applications (JoCAAA), 35(4), 28–40. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5262

Issue

Vol. 35 No. 4 (2026): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.