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More #BigData examples

Big Data

It’s time to new #BigData applications.

How Big Data is used by the London’s Tube

The first story is related to the London underground (you can read more here, and also in spanish:

The main objective when applying #Big Data is to imrpove the knowledge related to tube’s users, trying to offering the a better and more personalize information. Everything starts when a new user is registered on their website and he/she introduces his(her email. If this data is also geolocated, clients will receive information only related to where they are, for example, delays, without disturbing other clients that are not in the tube in this moment, because this information is useless if you don’t need it. Your information will be only to those clientes that really need that information, on a limit period of time. That way, users will be inform only for those incidents that could suffer.

Another use to the data is marketing, trying to link advertise and objective public, in a certain moment.

And, thanks to Big Data, the 2012 Olympic Games were a safer event for passanger, traing management, …

Iron Maiden, the rock band

Iron Maiden is a rock band created in the ’80, with more than 30 years on the music business, and who decided to use Big Data. One fact for doing that was that CD sells had dropped too much during the last years, so one of the leader of the band thought if there was a different way to meet their fans. Why not use the data used by P2P and Torrents to sketch the profile of the Iron Maiden fan? And going further, why not design the new Tour based on this information?

This is an atypical case of using negative data (anyway, it’s only data) to get positive information based on shered music. The results after the Tour ware extraordinary incredible: sold out tickets in almost all concerts, a big increase in merchandaising sells, more fans, …. and all thanks to p2p and BitTorrent data:

The case of 1004, from Telefónica

Telefonica, now Movistar, is the leader spanish telecommunication company in Spain. Their cliente attention service is called 1004, and by using #BigData and prediction models to the management, they got a reduction about 50% in errors and to manage between 1 and 5 millions users calls per months, reducing response time, and giving better service. You can read the complete story here (in spanish).

And … trat’s all for today!

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