Next at Microsoft podcast: Big Data being used to monitor, predict and provide real-time, real-world results

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Published onJune 16, 2015

published onJune 16, 2015

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In the latest Next at Microsoft podcast, Drew Purves from the Microsoft Research Ecology division and Jon Porter, Vice President of AccuWeather discuss the benefits of using Big Data and Microsoft’s Azure services to predict and give up-to-date statistics and tangible results. According to Purves,Big Data provides the agribusiness with useful information on their crop yield and what they can do to improve. He is able to get such information by building ecological models of crops and exposing them to hundreds of weather conditions. ForPurves, the predictions made in the models can be used to prevent possible crop eradication due to droughts or floods. You can listen to the latest podcast here:

Jon Porter argues that Global Food Security is of great concern and AccuWeather’s collaboration with Microsoft Research allows for real-time decisions to be made to prevent food shortage and provide results to individuals that have never had access to any sort of predictive data before.

This 4th podcast from Next at Microsoft reveals that Microsoft Research is working hard with their partners to help predict and monitor issues like climate change and food security in controlled conditions yet complete analytical processes for large scale environmental endeavors.

Radu Tyrsina

Radu Tyrsina has been a Windows fan ever since he got his first PC, a Pentium III (a monster at that time).

For most of the kids of his age, the Internet was an amazing way to play and communicate with others, but he was deeply impressed by the flow of information and how easily you can find anything on the web.

Prior to founding Windows Report, this particular curiosity about digital content enabled him to grow a number of sites that helped hundreds of millions reach faster the answer they’re looking for.

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Next at Microsoft podcast: Big Data being used to monitor, predict and provide real-time, real-world results