Machine Learning Models for Optimizing SAP-Based Data Processing in Cloud Environments

Abstract

The integration of Machine Learning (ML) models with cloud environments has revolutionized data processing, especially in enterprise systems like SAP. This research explores the use of ML algorithms to optimize SAP-based data processing in cloud environments, addressing challenges such as data integration, scalability, and performance. By applying various ML techniques such as regression analysis, clustering, and deep learning, the study aims to improve the accuracy and efficiency of data management tasks within SAP systems. Cloud platforms provide the computational power needed for processing large-scale datasets, while ML models enhance decision-making processes by identifying patterns, automating workflows, and predicting outcomes. The results show significant improvements in data processing speed, accuracy, and cost-effectiveness, offering businesses a scalable and efficient solution for managing SAP-based operations. This paper demonstrates how the convergence of ML and cloud computing can be leveraged to unlock new potential for enterprises using SAP systems.