We found it really interesting when using Tableau to determine the associations between the time, location, and the most popular apps. We thought about the ways that companies would be able to advertise to these users, and created a web application with this idea.

What it does

Our software allows companies to discover apps that are the most profitable to advertise on. We display a map that displays the users' hourly mobility, whether they're at home, commuting, or at work. We then show a tree map that visually represents a categorization of the apps based on their mobility.

How we built it

One section of the team worked on the front-end to visualize our app, while the other connected different data points together in order to create a usable table for the front-end to work with.

Challenges we ran into

1) One problem we faced was determining movement based on GPS coordinates due to a discrepancy in the number of points between the tables we wished to join. 2) Sleep

Accomplishments that we're proud of / What we learned

We're proud that we were able to connect the back-end of our app to the front-end, and also, to parse through the data and to be able to use that to come to conclusions. We were also glad to delve into D3.

What's next for SmartAds

The Big Leagues.

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