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Vol. 13 No. 01 (2026)
International Multidisciplinary Journal for Research & Development

Articles

The Convergence of Cloud Platformization and Artificial Intelligent Systems: A Multidimensional Framework for Scalable Enterprise Architecture and Predictive Analytics

Published 2026-01-31

  • Dr. Alistair Vance

Dr. Alistair Vance
Department of Information Systems and Digital Innovation, Stanford University

Abstract

The rapid evolution of cloud computing has transitioned from simple storage solutions to complex, integrated ecosystems that define modern enterprise agility. This research investigates the transformative value of cloud platformization, focusing specifically on the integration between scalable application environments like Heroku and robust Customer Relationship Management (CRM) systems such as Salesforce. By synthesizing the theoretical frameworks of decoupling, platformization, and recombination, this study explores how hybrid integration platforms and AI-powered data clouds are reshaping organizational efficiency. Furthermore, the paper delves into the application of supervised machine learning and time-series forecasting within these cloud environments, using heart disease prediction as a case study for high-stakes predictive analytics. The methodology employs a descriptive analysis of current architectural patterns, including the integration of legacy ERP systems and the mitigation of IoT-related cybersecurity threats. Results indicate that the synergy between elastic data engineering and automated security solutions significantly enhances marketing performance and operational resilience. The discussion highlights the shift from edge to cloud paradigms and the role of dynamic capabilities in leveraging big data analytics for competitive advantage.

Keywords

Cloud Platformization, Salesforce Integration, Machine Learning, Predictive Analytics

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References

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