📊 E-commerce Sales Dashboard (Power BI)

📌 Table of Contents

• Overview
• Objective
• Dataset Description
• Key Metrics (KPIs)
• DAX Measure
• Dashboard Features
• Visualizations
• Key Features
• Key Insights
• Tools & Technologies
• Dashboard Preview
• Conclusion
• Author

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🔹 Overview

This project is an interactive Power BI dashboard designed to analyze e-commerce sales performance. It provides insights into revenue, profit, customer behavior, and product performance using dynamic visualizations and filters.

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🎯 Objective

• Analyze sales and profit trends
• Identify profitable vs loss-making regions
• Understand customer purchasing behavior
• Evaluate category and sub-category performance

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📁 Dataset Description

🧾 Orders Table

• Order ID
• Customer Name
• State, City
• Order Date

📦 Details Table

• Amount (Sales)
• Profit
• Quantity
• Category / Sub-Category
• Payment Mode
• ADV (Average Value)

🔗 Tables are connected using Order ID

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📊 Key Metrics (KPIs)

• 💰 Total Sales (Amount)
• 📦 Total Quantity Sold
• 📉 Total Profit
• 📊 Profit Margin (%)
• 📈 Average Order Value (ADV)

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📐 DAX Measure Used

Total Sales = SUM(Details[Amount])

Total Profit = SUM(Details[Profit])

Total Quantity = SUM(Details[Quantity])

Profit Margin % = DIVIDE(SUM(Details[Profit]), SUM(Details[Amount]), 0)

Average Order Value = DIVIDE(SUM(Details[Amount]), DISTINCTCOUNT(Orders[Order ID]), 0)

Profit per Order = DIVIDE(SUM(Details[Profit]), DISTINCTCOUNT(Orders[Order ID]), 0)

Sales per Unit = DIVIDE(SUM(Details[Amount]), SUM(Details[Quantity]), 0)

Profit Category = 
IF(
    [Profit Margin %] > 0,
    "Profit",
    IF([Profit Margin %] < 0, "Loss", "Neutral")
)

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📈 Dashboard Features

🎛️ Filters (Slicers)

• State
• Category
• Order Date

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📊 Visualizations

• Profit Margin by State
• Profit by Month
• Quantity by Category
• Quantity by Payment Mode
• Profit by Sub-Category
• Sales vs Profit by State

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🎨 Key Features

• ✔ Interactive dashboard with slicers
• ✔ Conditional formatting (Red–Yellow–Green logic)
• ✔ Clean UI design
• ✔ Real-time filtering

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🧠 Key Insights

• Some regions are loss-making despite high sales
• Profit margins vary across states
• Certain categories have high volume but low profit
• COD & UPI are most used payment modes
• Monthly profit trends show fluctuations

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🚀 Tools & Technologies

• Power BI
• DAX
• Data Modeling

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🔹 Dashboard Preview

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🟢 Profit Scenario (High Performance)

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🔴 Loss Scenario (Business Issue Detection)

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📌 Conclusion

This dashboard helps in:

• Identifying loss-making regions
• Improving business decisions
• Enhancing profitability

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👤 Author

Sujan KS