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Big Data Hadoop in Criclytics

Now Navjot Singh Sidhu didn’t really say the words but I am pretty sure if he truly understood the implementations and uses of Hadoop in cricket itself apart from all the other fields then he is sure to say the very same words. Well Cricket isn’t an exact science but it is a numbers game and like any other scientific field it has factors and certain specific ones of these factors can help us get a very close to accurate reading to the performance of a certain player or even a team.

Cricket is almost a religion in India and holds a special place in the hearts of millions of international viewers. Knowing this it is paramount for ICC to implement better ways to resolve discrepancies in the outcome of any match. (Criclytics)Big Data Analysis in Cricket is fairly new yet thanks to technological advancements it has come a long way since its inception as third umpire to drones and bat sensors capturing each and every movement of the players in order to provide a fully enhanced virtual reality experience this Champions Trophy.

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Hawkeye, Snicko and HotSpot are the other most commonly used technologies in getting accurate results in any cricket match. All of these new technologies are built upon Criclytics. Take Wasp as an example, its prediction is based upon factors like the ease of scoring on the day according to the pitch, weather and boundary size. 7 hours before the 2015 World Cup final IBM made some very accurate predictions about its outcome by simply processing data. However, to better understand these advanced implementations one needs to be thorough with the fundamentals.

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If one takes a view of cricket from a broader spectrum the analogy makes it quite clear that everything from the team selection to the order in which a player performs it completely dependent on how the player has performed previously in all probable positions, which one is his strongest, which his weakest, his scores in terms of batting, bowling or even fielding and also what could be the strategy of the team opposing them. All these numbers are interpreted in terms of average data per match or as per entire season and the same procedure is repeated for every player of every team of of all the teams participating in any event such as the Championship Trophy. On the far side even though the process may seem a lot like only statistics, Criclytics provides a faster, cheaper and more efficient way to process all this data. CricBuzz, EspnCricInfo and CricApi are some of the best resources that provide data for Criclytics.

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Big Data in itself can’t do much instead it creates a few problems such as how to store such huge quantity of data and how to process the data. But thanks to Doug Cutting and Mike Cafarella Hadoop was created in 2005. The Hadoop Distributed File System(HDFS) was the much needed solution to both the problems that Big Data Generated. And as it was totally built upon java it even is compatible with a number of programming languages which made it the choice for any analysis job.

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But how to get started with such an amazing yet complex topic that is very much connected to our lives. For that you need to join a Big Data and Hadoop training. Asterix Solution provides the best training in Big Data and Hadoop Training in Mumbai which will make even a person who dislikes Maths love Hadoop. Big Data and Hadoop Training covers fairly advanced topics along with the guidance of experienced teachers who have had a lot of experience in the field. Visit the home page and contact us for more info regarding Big Data and Hadoop Training.