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This webinar aired April 29th, 2014 via Pivatol.

CLICK HERE TO WATCH VIDEO

Pivotal_case study on traffic big data image

(Note: Will be asked for an email address to watch)

As traffic volumes in cities around the world are constantly growing we are faced with the challenge to track and control car movements in a more detailed and intelligent way to beat the traffic. Real-time information on traffic including automotive sensors and crowd-sourced data feeds are an interesting new source of data. However, to utilize this data to its full extent and turn it into valuable information, intelligent methods for analyzing and predicting traffic are needed.

Learn how Pivotal’s Data Science Team has developed several methods to analyze traffic information from real-time data sources. Using a variety of methods on a massively parallel analytics database system, the team will also demonstrate a traffic disruption model that can predict the duration of recent incidents – learning the disruption patterns of a major city.

Learn how Pivotal is helping cities become smarter and more efficient. 

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Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.