A Modern Cloud-Native, Business Intelligence, Scalable Decision-Making in Data Analytics

Dr V Subrahmanyam, Dr M. V. Siva Prasad

Abstract: The exponential growth of data generated by enterprises, digital platforms, and IoT devices has made scalable decision-making systems an essential component of modern organizations. Traditional Business Intelligence (BI) solutions, although effective for descriptive analytics, face limitations in scalability, integration, and agility. Cloud-native BI solutions leverage distributed computing, containerization, micro services, and server less architectures to provide real-time, elastic, and cost-efficient analytics. This paper presents a comprehensive analysis of cloud-native BI solutions, their architectural design, integration with artificial intelligence (AI), and application in scalable decision-making. We propose a reference architecture that combines cloud-native services with advanced analytics pipelines, ensuring resilience, security, and interoperability across diverse data ecosystems. Experimental results demonstrate improvements in processing speed, scalability, and decision accuracy compared to legacy BI systems.

Keywords: Cloud-Native, Business Intelligence, Scalable Decision-Making, Data Analytics, Micro services, Server less, Real-Time Insights, Big Data

How to Cite?: Dr V Subrahmanyam, Dr M. V. Siva Prasad, "A Modern Cloud-Native, Business Intelligence, Scalable Decision-Making in Data Analytics", Volume 14 Issue 9, September 2025, International Journal of Science and Research (IJSR), Pages: 284-288, https://www.ijsr.net/getabstract.php?paperid=SR25908201535, DOI: https://dx.doi.org/10.21275/SR25908201535