Evolving BI Architectures: Integrating Big Data for Smarter Decision-Making

Authors

  • Suman Chintala Mechanicsburg, USA

Keywords:

Business Intelligence, Data Analytics, data processing, integration, spatial data analysis

Abstract

The integration of Business Intelligence (BI) with Big Data represents a significant advancement in how organizations process and analyze vast amounts of complex data to enhance decision-making. Traditional BI systems, while effective for structured data and historical analysis, struggle with scalability, flexibility, and real-time processing demands in today’s rapidly evolving data landscape. Big Data technologies offer solutions to these challenges, enabling organizations to manage large, diverse datasets and support real-time analytics. This article explores the evolution of BI, detailing architectural approaches such as Big Data-Enhanced ETL, Distributed Data Warehouse, Advanced Analytics, and Comprehensive Big Data Architectures. By analyzing each approach's benefits, limitations, and suitability, this article aims to provide organizations with the insights needed to leverage their data assets for strategic decision-making.

Published

2024-08-22

How to Cite

Chintala, S. (2024). Evolving BI Architectures: Integrating Big Data for Smarter Decision-Making. American Journal of Engineering , Mechanics and Architecture (2993-2637), 2(8), 72–79. Retrieved from http://grnjournal.us/index.php/AJEMA/article/view/5669