SuperMarket Sales Analysis — Interactive Excel Dashboard

This project analyzes 1,000 sales transactions from a supermarket chain operating across three branches (Alexandria, Cairo, and Giza) between January and March 2019. The goal is to transform raw, messy transactional data into a fully interactive dashboard that answers real business questions — the kind a manager or investor would actually ask.

🎯 Objectives

Practice a real-world BI workflow end-to-end, not just isolated Excel formulas

Turn a flat spreadsheet into a relational data model with proper relationships

Write reusable, dynamic DAX measures instead of static formulas

Answer 10 concrete business questions using data, not assumptions

Package everything into a single-screen, filterable dashboard

Data Cleaning (Power Query)

Real datasets are never perfect — here's what was actually fixed:

Verified no missing values and no duplicate transactions (1,000 unique Invoice IDs)

✅ Resolved a Branch/City mismatch in the source data (branch names didn't match their listed cities)

✅ Corrected the Time column's data type (was stored as plain decimal, not recognized as a proper time value)

✅ Removed a redundant "gross margin percentage" column — it was mathematically constant across every single row, so it added no analytical value

✅ Standardized text fields (trimmed whitespace, cleaned formatting)

🗄️ Data Model

Built a proper star schema in Power Pivot:

Fact Table

Dimension Table

Relationship: One-to-many

🧮 DAX Measures

❓ Business Questions Answered

💰 What are the total sales and profit by branch?

🛍️ Which product line generates the highest sales and quantity sold?

📈 What is the month-over-month sales growth trend?

👥 Do members spend more than normal customers?

⚖️ Is there a spending difference between male and female customers?

🧾 What is the average invoice value per branch?

💳 Which payment method is used most frequently?

🕐 What time of day sees peak sales activity?

🏆 Which branches offer the best overall investment potential?