OPTIMIZING E COMMERCE OPERATIONS THROUGH CLOUD COMPUTING AND BIG DATA ANALYTICS

The rapid expansion of e-commerce has led to a surge in data volume, requiring advanced technological solutions for efficient processing, analysis, and decision-making. This paper proposes a cloud-based framework integrated with big data analytics and predictive modeling to optimize e-commerce operations. The methodology involves systematic data collection, preprocessing, cloud storage integration, analytics, and predictive modeling using Train Neural Networks (TNN). insights and forecasts enable businesses to dynamically adapt to market conditions, improve customer satisfaction, and enhance operational performance. The experimental results, including an ROC curve with an AUC of 0.80, demonstrate strong classification accuracy, while consistent growth in cloud storage usage reflects system scalability. This work highlights the transformative potential of combining cloud computing and AI-driven analytics in addressing the challenges of modern e-commerce platforms.

Keywords: E-commerce, Cloud and Bigdata, TNN.