FMCG Sales Data Analysis Project using SQL

This project focused on analyzing Fast-Moving Consumer Goods (FMCG) sales data using SQL to generate business insights and support data-driven decision-making. The objective was to transform raw transactional data into meaningful information that could help stakeholders understand sales performance, customer behavior, and product trends.

The analysis included total sales, revenue, profit, product performance, customer purchasing patterns, regional sales comparisons, and time-based sales trends. SQL techniques such as joins, aggregate functions, grouping, filtering, subqueries, Common Table Expressions (CTEs), and window functions were used to answer business questions and produce actionable insights.

The findings highlighted the best-selling products, top-performing regions, highest-value customers, and periods of peak sales activity. The project also identified opportunities to improve inventory planning, optimize product offerings, and support strategic business decisions through data analysis.

Overall, the project strengthened practical SQL skills in database querying, data manipulation, and business intelligence while demonstrating the ability to analyze real-world FMCG data and communicate insights effectively.

Download full project on github:https://github.com/ShamimNandawula/FMCG_ANALYSIS