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27cbe7a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | # Sky Bound Global: Airline Performance & Analytics Dashboard
## π 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) β‘οΈ Data Modeling β‘οΈ Interactive Visualization.**
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## π οΈ Technical Stack
- **Data Preprocessing:** Python (Pandas, NumPy)
- **Data Visualization:** Power BI
- **UI Design:** Modern Glassmorphism / Dark Theme
- **Domain:** Aviation & Logistics
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## ποΈ 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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## π 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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## π₯οΈ 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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## π 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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## π€ Author
Mohammed Abo ellil
*Data Analyst | Python & Power BI Specialist* |