Appling Power BI for improved retail business analytics and decision-making

Huu DANG QUOC

doi:10.35784/acs_7130

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Published: Jun 28, 2025

DOI: https://doi.org/10.35784/acs_7130

Issue Vol. 21 No. 2 (2025)

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Appling Power BI for improved retail business analytics and decision-making
Huu DANG QUOC

154-163

DOI

https://doi.org/10.35784/acs_7130

Authors

Huu DANG QUOC

huudq@tmu.edu.vn

Thuongmai University, Hanoi, Viet Nam

https://orcid.org/0000-0001-5197-8066

Abstract

In the rapidly evolving retail industry, data-driven decision making is critical to maintaining competitive advantage and operational efficiency. This paper explores the diverse applications of Microsoft Power BI (MPBI) in retail, highlighting its impact on real-time data management, sales analysis, inventory optimization, customer insights, and supply chain performance. By synthesizing findings from recent studies and presenting empirical data from case studies, we demonstrate how Power BI's advanced analytics and visualization capabilities can transform raw data into actionable insights. Our research underscores the importance of integrating disparate data sources into a unified platform, facilitating comprehensive data analysis, and fostering a culture of data literacy across retail organizations. We also discuss the challenges and best practices for implementing Power BI across retail functions, highlighting its role in driving innovation and adapting to emerging market trends. The results of this study provide practical insights for retailers seeking to leverage data analytics for strategic decision-making and operational excellence.

Keywords:

retail data visualization, revenue and profit analysis, business intelligence tools, data-driven decision making

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DANG QUOC, H. (2025). Appling Power BI for improved retail business analytics and decision-making. Applied Computer Science, 21(2), 154–163. https://doi.org/10.35784/acs_7130

Appling Power BI for improved retail business analytics and decision-making

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