Retail Sales & Inventory Analysis

Project Overview

This project analyzes retail sales and inventory movement data to identify seasonal demand patterns, category contribution, and demand–supply gaps.

Tools Used

• SQL Server – Data cleaning & transformation
• Power BI – Interactive dashboard & visualization
• CSV – Data storage and transfer

Dashboard Highlights

• Monthly retail sales trend (seasonality analysis)
• Retail sales contribution by item type
• Demand vs warehouse supply comparison
• Interactive filters for year, item type, and supplier type

Data Preparation (SQL)

• Imported raw CSV data into SQL Server
• Classified suppliers into External vs Internal movements
• Handled NULL values safely during aggregation
• Exported analysis-ready dataset for Power BI

Key Insights

• Retail sales occur only in selected months, indicating seasonal demand
• Liquor, Wine, and Beer contribute the majority of retail sales
• Some categories show warehouse supply exceeding retail demand, indicating overstock risk

Dashboard Preview

Files in this Repository

• Retail_Sales.pbix – Power BI dashboard
• RETAIL_DATA_CLEANED.csv – Cleaned dataset
• RETAIL_WAREHOUSE.csv – Raw warehouse data
• SQL_RETAIL_SALES.sql – SQL queries for data preparation
• image.png – Dashboard screenshot

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Author: Karanveer Singh