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| # Sky Bound Global: Airline Performance & Analytics Dashboard | |
| ## 📊 Project Overview | |
| Sky Bound Global is a high-performance data analytics project designed to track and optimize airline operations. By processing a massive dataset of over 62 million flights, this project identifies patterns in flight efficiency, security risks, and logistics delays. | |
| The project follows a full data lifecycle: **Data Cleaning (Python) ➡️ Data Modeling ➡️ Interactive Visualization.** | |
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| ## 🛠️ Technical Stack | |
| - **Data Preprocessing:** Python (Pandas, NumPy) | |
| - **Data Visualization:** Power BI | |
| - **UI Design:** Modern Glassmorphism / Dark Theme | |
| - **Domain:** Aviation & Logistics | |
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| ## 🏗️ The Data Pipeline | |
| ### 1. Data Cleaning & Preprocessing (Python) | |
| Before any visualization, the raw data was processed using Python to ensure accuracy and speed. Key steps included: | |
| * **Data Integrity:** Handled missing values and standardized airport codes for 395 global airports. | |
| * **Feature Engineering:** Created calculated columns for "Lated Minutes" categorized by source (Weather vs. Security). | |
| * **Optimization:** Aggregated millions of rows of raw data to ensure the final dashboard remains responsive and fast. | |
| ### 2. Interactive Dashboards | |
| The dashboard is split into three primary analytical views: | |
| * **Executive Overview:** High-level KPIs tracking 62M+ flights and performance trends from 2014 to 2022. | |
| * **Company Analysis:** Benchmarking the top 21 airline carriers (Southwest, Delta, etc.) against cancellation rates and completion metrics. | |
| * **Flight Logistics:** A deep-dive into delay causes, identifying hubs like ATL and ORD as critical points for weather and security-related lated minutes. | |
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| ## 📈 Key Business Insights | |
| - **Total Scale:** Analyzed 62M flights, 1M cancellations, and 27K security situations. | |
| - **Efficiency:** Despite the high volume, the completion rate remains above 99% for top carriers. | |
| - **Delay Hotspots:** Identified specific airports where weather has a disproportionate impact on "Lated Minutes" compared to security. | |
| - **Safety:** Mapped safety trends across a decade to help stakeholders identify high-risk periods. | |
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| ## 🖥️ UI/UX Design | |
| The project features a custom-designed **"Start" Landing Page** and a vertical navigation rail. The dark-themed interface was specifically chosen to provide a professional, command-center aesthetic suitable for executive presentations. | |
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| ## 📂 Project Structure | |
| - `/python_scripts/`: Jupyter Notebooks/Python scripts for data cleaning. | |
| - `/dashboard/`: The .pbix / source visualization file. | |
| - `/assets/`: Background images and icons used for the UI. | |
| - `README.md`: Project documentation. | |
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| ## 👤 Author | |
| Mohammed Abo ellil | |
| *Data Analyst | Python & Power BI Specialist* |