Discover Data introduces students across the country to relatable, real-world applications of data and the professionals using that data to innovate the future.

In this self-paced eLearning module, students travel through a typical day to investigate everyday occurrences and discover where and how data and data science play a part.

Students will use archived Census data to explore changes in U.S. population density, diversity, and voting participation.

Students will investigate voting participation rates in elections, the impact of advanced data on campaign advertisements, and the evolving impact of media consumption and election information.

What holidays are you planning for right now? In these activities, students will have the opportunity to interact with national data, as well as collect data from family and friends, to draw conclusions about consumer behavior.

Students will assess the extent of the progress in 2020 by analyzing data through women’s changing role in entertainment, professional sports, and leadership.

Do you prefer to watch the game, the commercials or the halftime show? In these activities, students will investigate consumer data bytes surrounding championship football—such as the fans, the entertainment, and the food.

When companies “go green,” do they spend more or make more? There’s data for that, and these activities inspire students to think like innovators as they use data to solve environmental challenges.

How will the media habits of millennials change by the year 2050? In this activity, students will research how different audiences are consuming media and develop predictive models for what media habits will look like in 2050.

Why do some cars, clothing items or computers cost more than others? In this activity, students will look at perception data about luxury products and brainstorm with peers to create a luxury product prototype of their own.

If you’re a celebrity athlete, does your endorsement potential depend on winning games? In this activity, students will use data to predict how much potential an athlete has for being selected for ads and endorsements.

Data scientists are information engineers. These professionals are masters at making it easy for us to sort through mountains of data in order to get to a meaningful conclusion.