Length: 1 month of preparation and 7 hours of Hackathon
Content: MBA students teamed up with Data Scientists from GoodData. We were given public domestic flight data and 7 hours at the Hackathon to provide any insights that we’d like.
Data set: 47 million rows, 4GB, CSV file
Tools: We used R to build prediction model, Excel to deliver insights from historical data, and Google Slides for the presentation.
Our approach
Team meeting – MBA students: Determined our analysis focus (flight delays? cancellation? others?) and developed hypothesis.
Team meetings – MBA students and Data Scientists: Discussed about our analysis focus, agreed on the tools and amount of data we would use during the Hackathon
Hackathon:
I presented my idea of building a prediction model of flight cancellation.
My team agreed, and GoodData members helped to clean the data and build a multiple regression prediction model.
I came up with the creative recommendations about how flights search engines like Skyscanner could monetize from this model.
We presented our insights in terms of “Descriptive”, “Predictive” and “Prescriptive” Analysis.
