New Era’s Smart Systems and Internet Platforms Support Data Processing

Abstract

Over the past five years, Smart Systems, big data, and Internet-Based Computing have undergone significant convergence. Rather than treating these as independent technological silos, organizations increasingly integrate them into cohesive platforms that provide scalability and analytical depth previously unavailable. This paper analyzes how AWS, Azure, and Google Cloud have restructured their infrastructures to accommodate complex Automated Learning workloads and real-time analytical processing. Examining developments from 2020 to 2022, we identify five interconnected trends: emergence of cloud-native analytics stacks, automation expansion through Automated Model Building and low-code solutions, incorporation of IoT and digital twin frameworks, AI-driven security enhancements, and broader accessibility of advanced analytics capabilities. Despite these advantages, significant considerations arise regarding data governance, responsible AI deployment, and optimal resource allocation. Our analysis suggests that successful organizations will adopt balanced approaches integrating automated systems with sustained human judgment, particularly as these platforms penetrate deeper into mission-critical processes.