Unlocking the power of business intelligence in procurement with Power BI

In today’s fast-paced, data-driven business world, organizations rely heavily on advanced analytics and visualization tools to improve decision-making. This study explores the impact of business intelligence (BI) tools specifically Microsoft Power BI on analyzing procurement spending patterns. The primary goal is to determine how interactive dashboards can transform complex financial data into meaningful insights, aiding informed decision-making, cost management, and supplier performance evaluation. The research is based on established frameworks in business intelligence, data-driven decision-making, and technology adoption. It examines Power BI’s ability to integrate data from various sources, apply data-cleaning techniques, and utilize visualization tools such as bar charts, line graphs, and key performance indicators (KPIs) to present procurement data effectively. The study also explores the use of predictive analytics and anomaly detection to recognize spending trends and irregularities. Findings suggest that Power BI significantly improves procurement efficiency by providing real-time updates, automating reports, and enhancing transparency in financial transactions. However, the study also highlights challenges such as data integration issues, user adoption barriers, and security concerns related to handling sensitive financial data. This research contributes to the growing field of business intelligence in procurement analytics, offering practical recommendations for organizations seeking to optimize their spending strategies. Future studies could explore how AI-driven analytics and blockchain technology can further improve procurement transparency and efficiency.

Authors

Publication Details

Journal
International Journal of Research in Management
Published
2025-01-01
DOI
https://doi.org/10.33545/26648792.2025.v7.i1h.336
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Unlocking the power of business intelligence in procurement with Power BI

Akshay Shende, Juber Fattulal Naikwadi
1 citations
International Journal of Research in Management
Big Data and Business Intelligence
2.28
article

Unlocking the power of business intelligence in procurement with Power BI

Akshay Shende, Juber Fattulal Naikwadi
article en
1 citations

Abstract

In today’s fast-paced, data-driven business world, organizations rely heavily on advanced analytics and visualization tools to improve decision-making. This study explores the impact of business intelligence (BI) tools specifically Microsoft Power BI on analyzing procurement spending patterns. The primary goal is to determine how interactive dashboards can transform complex financial data into meaningful insights, aiding informed decision-making, cost management, and supplier performance evaluation. The research is based on established frameworks in business intelligence, data-driven decision-making, and technology adoption. It examines Power BI’s ability to integrate data from various sources, apply data-cleaning techniques, and utilize visualization tools such as bar charts, line graphs, and key performance indicators (KPIs) to present procurement data effectively. The study also explores the use of predictive analytics and anomaly detection to recognize spending trends and irregularities. Findings suggest that Power BI significantly improves procurement efficiency by providing real-time updates, automating reports, and enhancing transparency in financial transactions. However, the study also highlights challenges such as data integration issues, user adoption barriers, and security concerns related to handling sensitive financial data. This research contributes to the growing field of business intelligence in procurement analytics, offering practical recommendations for organizations seeking to optimize their spending strategies. Future studies could explore how AI-driven analytics and blockchain technology can further improve procurement transparency and efficiency.

International Journal of Research in ManagementVol. 7(1)
Openalex Percentile: Top 13%
Big Data and Business Intelligence
2.28
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