This project focuses on analyzing sales and operational data from an FMCG business to uncover insights that help improve profitability and decision-making.
Many FMCG companies generate large volumes of data from distributors, retailers, and online channels, but often lack clear visibility into what is actually driving revenue and profit. In this project, I collected and analyzed sales, product, and regional performance data to identify key business patterns.
Using Excel, Python, and Power BI, I cleaned and structured the data, performed exploratory analysis, and built an interactive dashboard to visualize business performance.
The dashboard highlights:
Sales performance by product category and SKU
Regional and channel-wise revenue trends
Top and underperforming products
Profit margin analysis
Monthly sales growth patterns
Through this analysis, the project identifies hidden gaps such as low-performing products, inefficient sales channels, and opportunities for revenue growth.
The final Power BI dashboard enables business managers to quickly monitor performance and make data-driven decisions regarding product strategy, distribution, and marketing investments.
Tools Used:
Power BI • Excel • Python • Data Cleaning • Data Visualization • Business Analytics
- Data Analyst