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📊 Sales Performance Dashboard

Author: Rehana Hassan Muhumed | IBM Data Analyst Certificate | April 2026

Python Pandas SQLite

🎯 Project Overview

Analyzed 9,994 sales transactions ($2.3M revenue) to identify profit drivers and provide recommendations.

📈 Key Findings

Metric Value
Total Sales $2.30 Million
Total Profit $286,397
Profit Margin 12.5%
Best Category Technology (18.5% margin)
Best Region West (15% margin)
Problem Area Furniture (-$1,000 loss)

💡 Top Recommendations

  1. Remove discounts over 30% - They lose money
  2. Fix Furniture pricing - Currently operating at loss
  3. Copy West region strategy to Central region

🛠️ Tools Used

Python (pandas, matplotlib, seaborn) | SQLite | Jupyter | Git

📁 Files

  • 01_sales_data_cleaning.ipynb - Data cleaning
  • 02_sales_analysis.ipynb - Charts & analysis
  • 03_sales_sql_queries.ipynb - SQL queries
  • 04_sales_dashboard.ipynb - Dashboard code
  • sales_dashboard.png - Main dashboard
  • sales_insights_dashboard.png - Insights dashboard

📊 Dashboard Preview

Dashboard

👩‍💻 Author

Rehana Hassan Muhumed

📅 Project Date

April 2026

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Sales performance analysis for Superstore dataset - Python, SQL, data visualization dashboard

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