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Real-Time Data Analytics Integration: A Technical Deep Dive

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  • Dileep Kumar Siripurapu

Abstract

Real-time data analytics integration represents a transformative approach to processing and utilizing data in modern organizations. This comprehensive article of real-time analytics systems explores the architectural foundations, implementation considerations, and industry applications that define successful deployments. The content delves into event-driven architectures, core components, and best practices that enable organizations to harness immediate insights from their data streams. The discussion encompasses performance optimization strategies, data quality frameworks, and fault tolerance mechanisms essential for robust real-time analytics systems. Industry-specific applications across financial services, healthcare, manufacturing, and retail sectors demonstrate the practical impact of real-time analytics in driving operational improvements and customer value. The exploration extends to emerging trends, including edge computing integration, AI/ML model deployment at the edge, quantum computing applications, and 5G network utilization, highlighting the evolving landscape of real-time analytics capabilities and their potential to reshape data processing paradigms across industries.

Suggested Citation

  • Dileep Kumar Siripurapu, 2025. "Real-Time Data Analytics Integration: A Technical Deep Dive," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 2484-2492, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:918
    DOI: 10.32628/CSEIT251112253
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112253
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