DataFest participants used over 17 million records of data related to job postings on Indeed's web site to gain insight into job markets over the course of a year across the US, Canada and Germany. Over 3 GB of data could be used to explore trends in job availability across months and seasons, to examine how users engaged with jobs in different industrial sectors, and to build analyses that could be used to help inform new job seekers. Many DataFest teams chose to combine Indeed's data with outside data on the economy and labor markets to help predict local, national and international economic activity.
DataFest participants used over 10 million records of hotel searches from Expedia’s web sites to analyze how customers interact with Expedia on their path from search to selection to purchase. Over 2 GB of search data could be combined with over 5 million fields of data describing travel destinations in order to understand how customer segments differ in their search and travel behavior and, ultimately, to help Expedia differentiate between “lookers”—those browsing Expedia’s sites—and “bookers”—customers who ultimately make a hotel reservation.
The inaugural DataFest at Ohio State. Participants used three data sets from TicketMaster—one with information about customer use of its web site, one describing events listed on the site, and one with information about Google ad campaigns on the site—to help understand how site visits could be converted to ticket sales, and to identify "true fans" of artists and bands.