AI/ML Powered Predictive Analytics in Cloud Based Enterprise Systems: A Framework for Scalable Data-Driven Decision Making
Keywords:
AI/ML-powered predictive analytics, cloud-based enterprise systemsAbstract
Business data-driven decision-making has been revolutionised by cloud computing, artificial intelligence, and machine learning. This paper presents a scalable, efficient, real-time AI/ML predictive analytics framework for commercial applications housed on clouds. Cloud-native data formats and artificial intelligence/machine learning models might let companies choose the cloud for scalability, adaptability, and processing capability. Data prep, model training, inference, and artificial intelligence/machine learning data lake/warehouse integration fall to clouds. Microservices, containerization, and Kubernetes help cloud-native applications grow, fail, and show great availability.
Predictive analytics in artificial intelligence/machine learning on cloud-based business systems might improve many processes. Our main uses include financial forecasts, customer behavior analysis, and supply chains optimization. Demand forecasting in artificial intelligence and machine learning, inventory control, and logistics planning might help to preserve supply chains by increasing efficiency. Machine learning systems may reveal customer behavior patterns for focused marketing and client retention. Predicting financial markets, asset pricing, and risk management, AI/ML models help to improve strategic financial planning and decision-making by means of their accuracy.
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