Demystifying Modern Business Intelligence Infrastructure: The Evolution to Cloud-Native, Globally Distributed Architectures

Gudipudi, Sujith (2025) Demystifying Modern Business Intelligence Infrastructure: The Evolution to Cloud-Native, Globally Distributed Architectures. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 2372-2380. ISSN 2582-8266

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Abstract

Business Intelligence infrastructure has undergone a revolutionary transformation from traditional on-premise deployments to sophisticated cloud-native architectures that span global regions. This evolution addresses fundamental limitations of legacy systems, including fixed capacity constraints, geographic boundaries, rigid scaling mechanisms, and complex disaster recovery procedures. Modern BI environments leverage cloud-hosted analytics engines, distributed data storage architectures, advanced identity management frameworks, and global deployment patterns to deliver insights with unprecedented speed and reliability. The shift toward containerized microservices enables independent scaling of components, while multi-region implementations ensure data availability across geographic boundaries. Organizations implementing these advanced architectures experience dramatic improvements in query performance, system availability, and resource utilization while simultaneously reducing operational costs. As enterprises increasingly adopt multi-tenant, multi-region designs, they gain resilience against regional outages, enhanced data sovereignty compliance, and the ability to serve global user populations with minimal latency. This architectural transformation fundamentally changes how organizations derive actionable insights from their data assets, positioning them for competitive advantage in an increasingly data-driven business landscape.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.3.1131
Uncontrolled Keywords: Architecture; Cloud-native; Governance; Microservices; Security
Depositing User: Editor Engineering Section
Date Deposited: 22 Aug 2025 07:15
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/4989