Thumalur, Amarnatha Reddy (2025) Recent advances in business intelligence: Transforming data into strategic insights. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 285-291. ISSN 2582-8266
![WJAETS-2025-0917.pdf [thumbnail of WJAETS-2025-0917.pdf]](https://eprint.scholarsrepository.com/style/images/fileicons/text.png)
WJAETS-2025-0917.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial Share Alike.
Abstract
This comprehensive article explores the transformative advancements in Business Intelligence (BI) that are revolutionizing how organizations leverage data for strategic advantage. The article examines five key technological developments reshaping the BI landscape: the integration of artificial intelligence and machine learning, the democratization of analytics through self-service platforms, the implementation of natural language processing for conversational data interaction, the emergence of augmented analytics systems that automate analytical workflows, and the migration to cloud-based BI infrastructures. Each innovation is examined through the lens of business impact, organizational transformation, and practical applications across diverse industry sectors. The article draws on insights from leading market analysts and implementation case studies to illustrate how these technologies are fundamentally altering organizational data cultures, analytical capabilities, and competitive positioning. It reveals how modern BI technologies have evolved from specialized technical tools to integrated business capabilities that enable more pervasive, timely, and sophisticated decision-making throughout organizations, establishing data-driven insights as a critical differentiator in today's rapidly evolving business landscape.
Item Type: | Article |
---|---|
Official URL: | https://doi.org/10.30574/wjaets.2025.15.3.0917 |
Uncontrolled Keywords: | Augmented Analytics; Self-Service Business Intelligence; Natural Language Processing; Cloud-Based Analytics; Artificial Intelligence Integration |
Depositing User: | Editor Engineering Section |
Date Deposited: | 16 Aug 2025 12:49 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4422 |