Optimizing SAP Data Processing with Machine Learning Algorithms in Cloud Environments
Abstract
This paper explores the optimization of SAP data processing through the integration of machine learning algorithms in cloud environments. As enterprises increasingly adopt SAP systems for enterprise resource planning (ERP), the complexity and volume of data generated have grown significantly, demanding more efficient processing methods. Traditional SAP data processing methods often struggle with scalability, speed, and real-time analytics. This research presents a solution that leverages cloud computing and machine learning techniques to enhance data integration, accelerate processing times, and improve decision-making. By applying machine learning models, such as regression, classification, and clustering algorithms, to SAP data, organizations can derive deeper insights, predict trends, and automate processes. The paper discusses various cloud platforms, such as AWS and Microsoft Azure, and evaluates their capabilities for supporting SAP data processing in conjunction with machine learning. The findings highlight the potential for significant improvements in data efficiency, business analytics, and operational performance.
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