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Enterprise Data Integration: A Case Study Analysis of Multi-Tenant Platforms Enabling Cross-Domain Analytics

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  • Swapnil Narlawar

    (Stevens Institute of Technology - Alumni, USA)

Abstract

This article explores the implementation case studies and performance analysis of centralized multi-tenant platforms across diverse industry sectors. The article analyzes enterprise-scale deployments in financial services, healthcare, and manufacturing, highlighting significant operational improvements achieved through well-designed architecture and implementation strategies. Key aspects explored include quantitative performance metrics spanning technical capabilities, reliability measures, and security parameters; user adoption patterns revealing critical success factors for organizational integration; and comprehensive cost-benefit analysis demonstrating compelling economic justification for these platforms. Through examination of real-world implementations, the article demonstrates how organizations leveraging Kubernetes-based multi-tenant architectures achieve substantial benefits in operational efficiency, service delivery timelines, and system maintenance costs. The findings reveal that successful implementations share common characteristics: modular architecture enabling incremental deployment, namespace-based isolation strategies with hierarchical resource quotas, and phased implementation approaches prioritizing high-impact functional areas. The article provides valuable insights for organizations considering multi-tenant platform adoption, offering both technical performance benchmarks and organizational adoption strategies to maximize implementation success and return on investment.

Suggested Citation

  • Swapnil Narlawar, 2025. "Enterprise Data Integration: A Case Study Analysis of Multi-Tenant Platforms Enabling Cross-Domain Analytics," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(4), pages 1079-1088, May.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:4:id:9748
    DOI: 10.32996/jcsts.2025.7.4.122
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