AI-Driven SAP HANA Cloud Framework for Medical Imaging and Social Media Platform Evaluation: Software Engineering Insights on Scalability, Security, and Automation
DOI:
https://doi.org/10.15680/IJCTECE.2023.0606012Keywords:
AI-driven systems, SAP HANA Cloud, medical imaging, social media analytics, scalability, security, automation, software engineering, cloud computing, machine learning, data governance, in-memory computing, Responsible AI, SAP BTP, AI governance, automated cloud security, ethical automation, risk management, compliance, explainability, enterprise systems, ML governance.Abstract
The integration of artificial intelligence (AI) with SAP HANA Cloud offers transformative potential for large-scale data processing and analytics within healthcare and digital communication domains. This study presents an AI-driven SAP HANA Cloud framework designed to enhance the performance, scalability, and automation of medical imaging systems and social media platform evaluation processes. Leveraging in-memory computing, predictive analytics, and machine learning models, the framework enables real-time insights from complex and heterogeneous datasets—ranging from diagnostic images to user interaction metrics. Emphasis is placed on software engineering principles governing modular design, microservices architecture, and continuous integration/continuous deployment (CI/CD) pipelines to ensure adaptability and maintainability. Additionally, the paper explores security mechanisms including data encryption, identity management, and compliance with healthcare data standards such as HIPAA and GDPR, ensuring trust and reliability. Performance benchmarking demonstrates that the proposed system achieves significant improvements in processing speed, scalability, and automation efficiency, positioning it as a viable model for next-generation AI-enabled cloud infrastructures in both medical and social media analytics contexts.
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