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🛠️ AMIT BI Performance Analysis

A Power BI dashboard designed to analyze business performance (2015-2017), visualizing revenue, profit, orders, and customer transactions for strategic decision-making.

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Project Details

🚀 Project Overview

This project, named AMIT BI, is a Power BI dashboard designed to analyze the performance of a business (likely a retail or e-commerce entity) over the years 2015-2017. The goal is to automate product data collection (revenue, profit, orders, and customer transactions) and visualize it into an interactive dashboard for further analysis. This project showcases data transformation skills.

This dashboard can be used by analysts, managers, or businesses to:

  • Track financial performance over time 📉📈
  • Compare product and customer performance 🔍
  • Collect structured data for market research 📊

🔧 Tech Stack & Libraries

Power BI 🖥️ Data Transformation 🛠️ Visualization 📊 Filters 🔍 CSV/Database 📑

📥 Data Extraction Workflow

Data Collection

Sourced from a structured dataset (likely CSV or database) containing sales, customer, and product details.

Data Transformation

Handled missing values and ensured consistency for accurate visualization.

Dashboard Creation

Designed multiple pages (Overview, Product, Customer Tooltip, Product Details) with:

  • ✅ Total Revenue and Profit
  • ✅ Customer Transaction Breakdown
  • ✅ Quantity Sold and Returned
  • ✅ Regional and Product Margin Analysis

Data Validation

Implemented filters and tooltips to manage missing elements, with debugging notes for refinement.

Save Results

Exported insights as interactive visuals and potential CSV exports for further analysis.

Columns include:

  • product_category
  • total_revenue
  • total_profit
  • total_orders
  • avg_order_value
  • returned_quantity
  • quantity_sold
  • margin
  • return_rate

📊 Example Use Case

For the AMIT BI dashboard, the analysis reveals:

  • Title → AMIT BI Performance Analysis Dashboard 🎨
  • Revenue → $25M
  • Profit → $10M
  • Top Customer → Jordan Turner ($15.6K) ⭐
  • Features → Interactive filters, regional breakdowns, and profit margins…
  • Description → Comprehensive view of sales, returns, and customer trends
  • Insights → Opportunities in Europe and weekend sales growth

📌 Key Learnings

  • ✔️ How to design interactive dashboards with Power BI
  • ✔️ Transforming multi-dimensional data into visual insights
  • ✔️ Best practices for handling missing data in visualizations
  • ✔️ Exporting clean datasets for advanced analysis

⚠️ Important Notes

  • Data reflects 2015-2017; real-time updates are recommended for current trends.
  • For production usage, consider integrating live data sources to handle dynamic content and ensure accuracy.

🌟 Why This Project Matters

This project demonstrates real-world business intelligence skills that can be applied in:

  • E-commerce Performance Tracking
  • Market Trend Analysis
  • Strategic Decision Support
  • Customer Segmentation

It's a solid foundation for data-driven decision-making in retail and marketing.

📋 Recommendations

  • ✔️ Improve Product Quality in Europe: Address the 33.33% return rate by enhancing product standards or customer support in this region. 🔧
  • ✔️ Boost Weekend Sales: Launch targeted marketing campaigns to increase the 28.57% weekend order share, potentially doubling weekend revenue. 📈
  • ✔️ Optimize Low-Margin Products: Review "L Road Frame" and "LL Touring Frame" for cost efficiency to improve overall margins. 💡
  • ✔️ Enhance Customer Loyalty: Develop tailored loyalty programs for top customers like Jordan Turner to sustain high-value transactions. 🤝
  • ✔️ Integrate Live Data: Update the dashboard with real-time data sources for dynamic insights beyond 2017. ⏳

👨‍💻 Author

Developed by Abdelrahman Haroun

👉 If you like this project, give it a ⭐ on GitHub!