An SAP-Driven AI and Azure-Based Big Data Analytics Framework for Secure Cloud and Broadband-Enabled Enterprises
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Abstract
The convergence of SAP‑driven artificial intelligence (AI) with Azure‑based business intelligence (BI) presents transformative opportunities for enterprise digital platforms that require secure, scalable, and broadband‑enabled operations. As cloud adoption accelerates and broadband connectivity becomes ubiquitous, enterprises are investing in integrated platforms that combine enterprise resource planning (ERP), predictive analytics, and decision support to drive efficiency, resilience, and competitive advantage. However, such integration raises critical challenges related to cloud security, real‑time analytics, data privacy, and system interoperability. This paper proposes a cohesive architectural framework that leverages SAP’s AI capabilities alongside Azure’s BI ecosystem to enhance operational intelligence while ensuring robust cloud security for broadband‑enabled enterprise environments. The framework emphasizes automated threat detection, identity governance, predictive analytics, and real‑time dashboards that aggregate structured and unstructured data across enterprise systems. A mixed‑methods evaluation using simulated enterprise workloads demonstrates significant improvements in detection accuracy, analytical transparency, and decision timeliness. Findings indicate that enterprises can achieve secure, high‑performance analytics without compromising compliance, and that SAP–Azure integration enhances data governance and operational readiness. The study contributes a validated model for enterprises seeking to balance advanced analytics with cloud security in an era of ubiquitous broadband connectivity.
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