Edge Computing Integration for Real-Time Analytics and Decision Support in SAP Service Management

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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Publication Details

Journal
International Journal for Research Publication and Seminars
Published
2025-06-05
DOI
https://doi.org/10.36676/jrps.v16.i2.283
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.49
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article

Edge Computing Integration for Real-Time Analytics and Decision Support in SAP Service Management

Nidhi Yadav
1 citations
International Journal for Research Publication and Seminars
IoT and Edge/Fog Computing
1.49
article

Edge Computing Integration for Real-Time Analytics and Decision Support in SAP Service Management

Nidhi Yadav
article en
1 citations

Abstract

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.

International Journal for Research Publication and SeminarsVol. 16(2)
Deloitte (United States) (US)
Openalex Percentile: Top 15%
IoT and Edge/Fog Computing
1.49
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