Architecting Intelligent Cloud Platforms for Enterprise Analytics Using Event Driven Data Processing and AI Automation
DOI:
https://doi.org/10.15662/IJARCST.2025.0806032Keywords:
Enterprise Analytics, Event-Driven Architecture, Cloud Computing, Artificial Intelligence, AI Automation, Event Streaming, Real-Time Data Processing, Cloud-Native Platforms, Machine Learning, Predictive Analytics, Microservices, Serverless Computing, Data Engineering, Business Intelligence, Intelligent AutomationAbstract
The rapid evolution of digital enterprises has generated unprecedented volumes of real-time data from business applications, Internet of Things (IoT) devices, customer interactions, financial systems, and cloud-native services. Traditional batch-processing architectures often fail to deliver the responsiveness and scalability required for modern enterprise analytics. This research proposes an intelligent cloud platform that integrates event-driven data processing with Artificial Intelligence (AI) automation to enable real-time enterprise analytics, intelligent decision-making, and operational optimization. The proposed framework utilizes event streaming, cloud-native microservices, serverless computing, distributed messaging systems, and AI-driven automation to process continuous data streams with minimal latency. Machine learning and deep learning algorithms analyze streaming events to identify business trends, detect anomalies, forecast operational outcomes, and automate enterprise workflows. AI-powered orchestration continuously optimizes cloud resources, prioritizes critical events, and initiates autonomous responses to changing business conditions. Furthermore, the framework incorporates cloud governance, security, data quality management, and scalable analytics services to ensure reliable enterprise intelligence and regulatory compliance. By combining event-driven architecture with AI-enabled automation, organizations can improve operational efficiency, accelerate business intelligence, reduce processing delays, and strengthen digital resilience. The proposed architecture provides a scalable, intelligent, and adaptive enterprise cloud platform capable of supporting real-time analytics, predictive decision support, and continuous innovation across diverse business environments.References
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