Real-Time Data Analytics Integration: A Technical Deep Dive
DOI:
https://doi.org/10.32628/CSEIT251112253Keywords:
Real-time Analytics Integration, Event-Driven Architecture, Edge Computing, Data Quality Management, Performance OptimizationAbstract
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.
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References
D. Reinsel, J. Gantz, and J. Rydning, "The Digitization of the World From Edge to Core," 2018. Available: https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf
W. Gitonga, "Real-time data analytics Transforming Decision-Making in the Digital Age," 2024. Available: https://www.linkedin.com/pulse/real-time-data-analytics-transforming-decision-making-wilson-gitonga-nggsf
Amazon Web Services (AWS), "What is an Event-Driven Architecture?," 2024. Available: https://aws.amazon.com/event-driven-architecture/
S. Wilkes, "Best Practices for Real-Time Stream Processing," 2024. Available: https://www.striim.com/blog/6-best-practices-for-real-time-data-movement-and-stream-processing/
F. Z. Rozony, "A Comprehensive Review Of Real-Time Analytics Techniques And Applications In Streaming Big Data," 2024. Available: https://www.researchgate.net/publication/386874324_A_Comprehensive_Review_Of_Real-Time_Analytics_Techniques_And_Applications_In_Streaming_Big_Data_FZ_Rozony
F. Reghenzani, et al., "Software Fault Tolerance in Real-Time Systems: Identifying the Future Research Questions," 2023. Available: https://dl.acm.org/doi/full/10.1145/3589950
Psico, "The Impact of RealTime Data Analytics on Business Performance Metrics," 2024. Available: https://psico-smart.com/en/blogs/blog-the-impact-of-realtime-data-analytics-on-business-performance-metrics-167845
StarTree, "Real-Time Analytics: A Comprehensive Guide," StarTree Resources, 2024. Available: https://startree.ai/resources/real-time-analytics-a-comprehensive-guide
C. Pettey, "6 Best Practices for Real-Time Analytics," 2024. Available: https://www.gartner.com/smarterwithgartner/six-best-practices-for-real-time-analytics
Middleware.io, "10 Observability Best Practices Every DevOps Should Implement," 2025. Available: https://middleware.io/blog/observability/best-practices/
K. Chhablani, "Edge Computing: The Future of Real-Time Data Processing," 2024. Available: https://medium.com/@kiran_c/edge-computing-the-future-of-real-time-data-processing-3fa8a98099ef
N. S. Gill, "Edge AI and 5G Integration," 2024. Available: https://www.xenonstack.com/blog/edge-ai-and-5g-integration
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