Sales and Profitability Analysis of a US Superstore Using Power BI

Abstract

The present study examines the sales and profitability performance of a US Superstore using Business Intelligence and Data Analytics tools, particularly Microsoft Power BI and Microsoft Excel. The study aims to analyse sales trends, profitability patterns, customer segments, regional performance, shipping modes, and product categories to generate meaningful business insights. Secondary data obtained from the US Superstore Sales Dataset available on Kaggle were used for analysis. Data cleaning, transformation, visualization, and interpretation techniques were applied to identify significant patterns and business opportunities. The findings reveal that the Consumer segment contributes the highest share of sales, while Technology and Furniture are among the most significant revenue-generating product categories. Regional analysis indicates noticeable variations in sales performance across geographical locations, and monthly trend analysis highlights fluctuations in sales and profitability over time. The study demonstrates how Business Intelligence tools can transform large datasets into meaningful visual information that supports strategic decision-making and operational improvement in the retail sector.

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DOI & Citation