Optimizing Cloud Data Architectures through Predictive Modeling

Joseph Aaron Tsapa

Abstract: This review focuses on applying predictive modeling in data architecture optimization on the cloud. Amid the data growth story and the dawn of cloud computing, it is essential to design a system that will perform well, scale to the demands of consumers, and simultaneously be within the budget. The predictive modeling methodologies provide nuances of future trends, allow an organization to avoid problems, and explicitly design data architectures accordingly and proactively. In this paper, the topic of suboptimal cloud data architecture is considered, and a solution is proposed using predictive modeling. The importance of it is explained, its contribution to the achievement of goals is touched, and the prospects of the overall topic are specified for further investigation.

Keywords: Cloud data architectures, predictive modeling, optimization, scalability, cost-effectiveness