The aim of this project is to reveal insights into the main causes of air crashes and other aviation accidents, with a focus on understanding how these can be prevented in future. Analysis is performed on various attributes within the data files by implementing a end-to-end data pipeline in AWS. This pipeline merges data files and transforms all necessary rows and columns for final analysis. Some of the columns focused on are accident location, number of injuries sustained, weather conditions, and aircraft design details like type, make, model, among other relevant factors. Finally, a Tableau dashboard was created to visualize the results of the analysis.
- Designed data architecture pipleine to enable seamless data integration and flow for analysis on cloud.
- Developed automated ETL workflows to optimize data transformation processes.
- Analyzed and visually represented the severity, causes, and seasonal trends of aviation accidents in the United States.
- Data Storage - Microsoft Excel, AWS S3
- ETL - AWS Glue Studio, Glue Database
- Analysis & Visualization - Amazon Athena, SQL, Tableau