BUSINESS INTELLIGENCE IN THE ERA OF BIG DATA: A REVIEW OF ANALYTICAL TOOLS AND COMPETITIVE ADVANTAGE

This paper looks at how Business Intelligence (BI) tools have changed over time. It starts with simple query and reporting functions and moves to predictive analytics, machine learning, and data‑processing systems that can scale up. The authors examine how these tools work in Big Data settings. They show that BI can give a complete picture of market trends, consumer habits, and how efficiently a company runs. When BI is combined with Big Data analytics, companies can make faster, data‑driven decisions and gain a competitive edge. Because the article is a review, it does not include detailed experiments that test each tool under different network loads or with mixed data formats.

For M.Tech students, the paper offers a solid starting point for building comparative simulation frameworks. It suggests how to set up evaluation metrics that compare BI tools—such as Apache Spark, PowerBI, and Tableau—based on scalability, latency, and processing efficiency. Fried Engineers can help students with project development, component selection, and guidance on structuring the comparison, creating simulation pipelines, and documenting the architectural analysis.

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