From Business Intelligence to Intelligent Analytics: Evolution of Enterprise Data Platforms

Authors: JAGADEESWAR ALAMPALLY

DOI: https://doi.org/10.37082/IJIRMPS.v11.i4.232966

Short DOI: https://doi.org/hbq6wk

Country: United States

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Abstract: Enterprise analytics has undergone significant transformation, evolving from centralized business intelligence systems focused on static reporting to dynamic, AI-driven intelligent analytics ecosystems. Traditional BI platforms, built upon data warehouse architectures and structured query processing, primarily supported descriptive and diagnostic analytics. However, the rapid growth of big data technologies, distributed computing frameworks, and artificial intelligence has reshaped enterprise data platforms into scalable, adaptive, and predictive environments. This paper examines the architectural evolution from conventional BI infrastructures to intelligent analytics ecosystems. It analyzes transitional patterns in enterprise modernization, including the emergence of data lakes, cloud-native platforms, real-time processing frameworks, and integrated machine learning pipelines. The study further identifies key architectural considerations and organizational challenges associated with migrating legacy systems to AI-ready platforms. By synthesizing foundational literature on business intelligence, big data, and artificial intelligence, this research proposes a structured view of enterprise analytics transformation and outlines strategic implications for organizations seeking sustainable competitive advantage through intelligent data capabilities.

Keywords: Business Intelligence, Intelligent Analytics, Enterprise Data Platforms, Big Data Architecture, Artificial Intelligence, Data Warehousing, Cloud Analytics, Enterprise Modernization

Paper Id: 232966

Published On: 2023-07-01

Published In: Volume 11, Issue 4, July-August 2023

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