Overview

The Skytrax Global Airlines Analytics Project is an innovative initiative designed to transform how we analyze customer feedback for airlines. By leveraging modern cloud services and industry-standard technology, it offers an end-to-end process for not just collecting reviews but also processing and visualizing the data. This project aims to provide actionable insights into customer satisfaction, operational efficiency, and overall competitiveness within the airline industry, making it an invaluable tool for stakeholders.

With an architecture that meticulously combines data extraction, transformation, and analysis, this project stands out by utilizing the vast amount of information available from customer reviews on Skytrax. It focuses on providing directional insights rather than definitive conclusions, acknowledging the nature of self-reported data. In doing so, it caters to specific user needs while maintaining clarity in data interpretation.

Features

• Modular Data Cleaning: Utilizes Python functions to clean and standardize raw scraped data, ensuring high data quality for subsequent analysis.
• Efficient Review Scraping: Automates the collection of customer reviews from Skytrax, staging the data in S3 for easy access and processing.
• Advanced Data Transformation: Employs CI/CD workflows with dbt-based transformations on Snowflake, ensuring continuous integration and deployment.
• Interactive Dashboard: Features a web-based dashboard that visually presents insights derived from airline reviews, making data easily digestible.
• Robust Technology Stack: Built on a powerful combination of Python, Apache Airflow, AWS S3, and Docker, ensuring scalability and reliability.
• Team Collaboration: Supported by a diverse team of analytics engineers, data scientists, and software developers, promoting a collaborative approach to project objectives.
• Focus on Actionable Insights: Aims to derive insights that guide decision-making, particularly in understanding customer sentiment and airline performance metrics.