Intelligent Enterprise Data Platforms with Autonomous Analytics and Artificial Intelligence Driven Cloud Orchestration for Optimization
Abstract
The rapid digital transformation of enterprises has significantly increased the volume, variety, and velocity of organizational data, necessitating intelligent data platforms capable of supporting autonomous analytics and artificial intelligence (AI)-driven cloud orchestration. Traditional enterprise data management systems are increasingly unable to address the dynamic demands of modern business environments characterized by distributed cloud infrastructures, heterogeneous data sources, and continuously evolving operational requirements. This research investigates an intelligent enterprise data platform that integrates autonomous analytics with AI-driven cloud orchestration to optimize resource utilization, decision-making, operational efficiency, and business agility. The proposed framework combines machine learning, predictive analytics, intelligent workflow automation, edge computing, cloud-native architectures, and autonomous resource management to enable continuous monitoring, adaptive optimization, and real-time decision support. AI algorithms analyze enterprise data streams, predict workload fluctuations, allocate cloud resources dynamically, and automate infrastructure management with minimal human intervention. The study adopts a comprehensive research methodology involving literature synthesis, architectural framework development, simulation-based evaluation, and performance analysis. Expected outcomes include improved scalability, enhanced system reliability, reduced operational costs, faster analytical processing, stronger security compliance, and optimized cloud utilization. The research contributes to the advancement of intelligent enterprise ecosystems by demonstrating how autonomous analytics and AI-driven orchestration collectively improve enterprise competitiveness, resilience, and sustainable digital transformation in increasingly complex cloud computing environments
Article Information
Journal |
International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
|---|---|
Volume (Issue) |
Vol. 8 No. 5 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) |
DOI |
|
Pages |
17303-17312 |
Published |
October 10, 2025 |
| Copyright | |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Chetan Sasidhar Ravi (2025). Intelligent Enterprise Data Platforms with Autonomous Analytics and Artificial Intelligence Driven Cloud Orchestration for Optimization. International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , Vol. 8 No. 5 (2025): International Journal of Advanced Engineering Science and Information Technology (IJAESIT) , pp. 17303-17312. https://doi.org/10.15662/IJAESIT.2025.0805013 |
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