Real-Time Data Processing in Cloud Computing: Enterprise Implementation Strategies
DOI:
https://doi.org/10.32628/CSEIT251112134Keywords:
Cloud Computing, Real-time Data Processing, Enterprise Architecture, IoT Integration, Scalability PatternsAbstract
This article examines the transformative impact of real-time data access enabled by cloud computing across enterprise organizations, focusing on implementation strategies and architectural patterns. Through detailed analysis of industry-leading case studies, this article explores how cloud-based real-time data processing solutions have revolutionized business operations and customer experiences. This article investigates critical technical components including data streaming architectures, IoT integration, geospatial processing, and predictive analytics implementations. This article demonstrates that successful real-time data processing implementations require careful consideration of infrastructure requirements, scalability patterns, and performance optimization strategies. This article provides insights into common challenges such as handling peak loads, ensuring data consistency, and maintaining system reliability, while also examining emerging trends in edge computing and artificial intelligence integration. This article contributes to the growing body of knowledge on enterprise-scale real-time data processing and offers practical guidance for organizations planning similar implementations.
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