Authors: Sudhir Vishnubhatla
Abstract: As financial and digital enterprises adopt cloud-native big-data systems, the focus has shifted from feasibility to cost-effectiveness. Elastic compute, multi-tiered storage, and managed services have removed barriers to scalability but introduced new challenges of cost predictability, governance, and optimization. This article synthesizes two decades of research and practice to articulate cost-optimization strategies for big-data systems in the cloud. It frames cost not as a narrow technical knob but as a discipline spanning architecture, governance, lifecycle management, and multi-cloud alignment. Three diagrams, the cost optimization model, the iterative cost lifecycle, and the levers of cost control—are used to illustrate how modern organizations can manage the financial sustainability of their big-data ecosystems without sacrificing agility, resilience, or compliance
DOI: http://doi.org/10.5281/zenodo.17452344
