This project involves analyzing over 5 million records of commercial airline flights from the year 2015. These records, compiled for the U.S. Department of Transportation (DOT) Air Travel Consumer Report, include details such as airline names, flight numbers, origin/destination airports, flight distance, and scheduled versus actual departure and arrival times.
The recommended analysis for this dataset involves answering several questions:
- Variation in overall flight volume by month and day of the week.
- The percentage of flights that experienced a departure delay in 2015, along with the average delay time in minutes for those flights.
- Variation in the percentage of delayed flights throughout the year, with a specific look at flights leaving from Boston (BOS).
- The number of flights that were canceled in 2015, including the percentage of cancellations due to weather and those due to the airline/carrier.
- Identification of the most and least reliable airlines in terms of on-time departures.
- The approach to this analysis involves processing 5.82 million rows of data across 30 fields to uncover insights about flight volume variations, departure delay percentages and times, cancellation causes, and the reliability of different airlines.
This process covers everything from data extraction, transformation, and loading (ETL) to visualization, with data sourced from Kaggle.
The desired outcome is an improved understanding of flight volume and delays, which will enhance operational efficiency and inform decision-making. This analysis is presented in a Power BI report comprising four pages, each designed to convey different aspects of the data:
- Summary Dashboard
- Delay by Airline Company
- Detailed Delay Time
- Delay by Airport
The data should be clean and the report should be able to refresh to include any new files added to the Kaggle website. The data source provided for this project is the Kaggle dataset available at https://www.kaggle.com/datasets/giovamata/airlinedelaycauses.