Enter the Travel-Verse

The past few years represent the best and worst in air travel in decades. 2019 saw the best year for air travel this century while the pandemic brought long periods of extreme swings in demand. ARC’s data is the world’s largest single source of airline ticketing data.

The goal is to identify a trend that leads to a new prediction using ARC’s data to incorporate it into a marketable data product within the B2B or B2B2C space.

Your task is to find creative ways to apply the vast data store from historical trends mapped into predictive analytics to specific recommendations for consumers and suppliers of air travel — the potential has no limit.

The Challenge 

• Review the provided airline ticketing dataset below Identify a problem in the travel and tourism industry where advanced awareness of current and future trends using airline ticketing data will solve. 
• Identify the audience in the B2B or B2B2C space that would find value in the solution. 
• Using Machine learning, data science technologies and/or advanced analytics to develop a solution that solves the problem that you have identified and defined. (For example, recommender systems, predictive analytics, etc.) 
• Create an application prototype (program, website, API etc.) and/or visual aid (such as a dashboard or video presentation) to demonstrate the business value of the proposed solution.

Dataset details

Data provided: There are 2 sample sets available which contain historical global air travel ticketing data to work with.

• Dataset - Sample: TravelVerse Sample Dataset
• Smaller representative sample which provides more flexibility

• Dataset – Large (compressed):  TravelVerse Large Dataset
• Larger sample size, requires decompression and may require advanced tools and processing

 Dataset Overview: Data Glossary

Here is a webinar to understand more about the ARC dataset

 Note: You can use any available external sources of data to merge with this dataset. Sample sources could include weather, social media, publicly sourced data, etc. 

Resources

ARC’s data trends: https://www.youtube.com/c/AirlinesReportingCorporation 

Note: You can use any available external sources of data to merge with this dataset. Sample sources could include weather, social media, publicly sourced data, etc. 

Reach out to archackathonteam@arccorp.com for any queries regarding the dataset.