This project analyzes retail sales data to uncover insights on revenue, profitability, and product performance using SQL and Power BI. Sales Data Analysis Project

📌 Project Overview

This project analyzes sales performance for a retail business using SQL and Power BI to uncover key insights into revenue, profitability, and product performance.

🎯 Business Problem

The business wants to understand:

• Which products generate the most revenue and profit
• Which regions perform best
• How discounts impact profitability
• Key trends in sales over time

🛠 Tools Used

• SQL (Data Cleaning & Analysis)
• Power BI (Data Visualization)
• Excel (Data Handling)

📊 Dataset

The dataset contains 9,994 records including:

• Orders
• Products
• Sales
• Profit
• Discounts
• Customer and regional data

🔍 Data Cleaning

• Standardized column names
• Verified data types
• Checked for missing values and duplicates

📈 Key Insights

1. Regional Performance

• West region generates the highest sales and profit
• South region underperforms compared to others

2. Category Performance

• Technology is the most profitable category
• Furniture generates high sales but very low profit

3. Discount Impact

• Products sold without discounts generate the highest profit
• High discounts significantly reduce profitability

4. Product Performance

• Canon imageCLASS 2200 Advanced Copier is the most profitable product

💡 Business Recommendations

• Focus marketing efforts on high-performing regions (West & East)
• Reduce excessive discounting strategies
• Re-evaluate pricing for Furniture category
• Increase inventory for top-performing products

📊 Dashboard

📊 Dashboard Preview

The Power BI dashboard provides:

• Sales overview (KPIs)
• Regional performance
• Category insights
• Monthly trends
• Product-level profitability

✅ Conclusion

The analysis highlights key revenue drivers and areas of improvement, helping the business make data-driven decisions to increase profitability.