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On your marks to win the Big Data race!
During the London 2012 Olympics, Atos is processing 30% more data compared to the data processed during Beijing 2008 Olympic Games. And this refers exclusively to what is considered “structured data”, data generated inside the Olympic venues: results, statistics, participant biographies and related stories and news… To measure the increase in terms of “unstructured data” generated around the Olympics events in Social Networks and Social Media when compared to 4 years ago is a big task…
Data has now to be made available to end users in real-time. On one hand, as usual, broadcasters assisting to the event need this information for their commentaries on live broadcast. But the new challenge is that with the rise of smart mobile devices, fans expect to have information available immediately as well wherever they are. This has significant implications in the way data needs to be processed and correlated.
What can we anticipate to happen in 2016, during the Rio Games?
- Firstly, we can expect there will be a significant increase in the volume of structured data coming from the Olympic venues: All sorts of technologies (biometrics, image recognition, sensors) are providing more information related to athletes performance on the field of play, as well as all sorts of contextual data (weather conditions, ball position, …)
- Secondly, fans will expect to have additional contextual information enriching the information they will be receiving. And Social Network and Social Media contents should play a significant role adding value to the structured data: on the one hand, discriminating relevant structured data (for example, what points in a tennis match where actually preferred by spectators) and on the other hand enriching the structure data with images, videos, sentiment analysis.
The ability to manage all this information will revert in an enhanced experience for fans and event spectators. The entire viewing experience will be improved with advanced graphical representation techniques, ranging from 3D representations to predictive analysis, etc.
The challenge technology is facing now is how to manage and correlate all this data in a way that can be useful and enrich the spectator and fan experience. Big Data Analytics will provide the means to correlate all this information.
But sport and Olympics is only an example of what we can expect in many other fields of information processing, which will develop enhanced services for end users by managing increasing amounts of data. We can easily identify other examples such as traffic and crowd control, healthcare applications, etc. So, on your marks to win the Big Data race!