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Research demonstrates improved real-time analytics and decision support in SAP Service Management, suggesting edge computing may enhance service efficiency.
The integration of edge computing with enterprise solutions like SAP Service Management holds a disruptive potential of real-time analytics and decision support but remains under-leveraged in current research. Current SAP architectures rely on centralized cloud processing, introducing latency, bandwidth restrictions, and reduced responsiveness for mission-critical service processes. Current research has been focused on SAP workflow optimization through cloud boosting or AI-driven analytics without leveraging the potential of decentralized edge infrastructures for enhancing decision-making time and data granularity. The present research addresses the missing link by investigating how edge computing can be strategically integrated into SAP Service Management to enhance real-time monitoring, predictive maintenance, and adaptive service provisioning.
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Nidhi Yadav (2025) studied this question.
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