Over the next several weeks, Concur #BigData analyst Denny Lee will share his technical insights into the world of data analysis and big data management in the world of travel and expense. From time to time he will offer some interesting approaches to viewing data so that you can see the world of information that our data scientists encounter every day.
As part of some quick analysis of flight departure data, to more quickly understand the impact of distance, date, and time of day on departure delays, I recently forked the Square Crossfilter and incorporated data from RITA BTS Flight Departure Statistics and Great Circle Mapper to calculate airport distances. What's interesting about this data is that it shows you statistical patterns of arrival times (and delays) for different days of the month and week. At the bottom is a nice screenshot of the results, but you can interact with the data directly by clicking any of the links directly below. Please note that it will take a few seconds to a few minutes to load up because of the large files d3 will process. Have fun!
- Airline On-time Departure Performance (Top 15 US Cities)
- Airline On-time Departure Performance (Full, Codepen)
- Airline On-time Departure Performance (Full, AWS)