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Big Data is emerging from the realms of science projects at Web companies to help companies like telecommunication giants understand exactly which customers are unhappy with service and what processes caused the dissatisfaction, and predict which customers are going to change carriers. To obtain this information, billions of loosely-structured bytes of data in different locations need to be processed until the needle in the haystack is found. The analysis enables executive management to fix faulty processes or people and maybe be able to reach out to retain the at-risk customers. The real business impact is that big data technologies can do this in weeks or months, four-or-more-times faster than traditional data warehousing approaches.
The IT techniques and tools to execute big data processing are new, very important and exciting.

The advent of the Web, mobile devices and other technologies has caused a fundamental change to the nature of data. Big Data has important, distinct qualities that differentiate it from �traditional� corporate data. No longer centralized, highly structured and easily manageable, now more than ever data is highly distributed, loosely structured (if structured at all), and increasingly large in volume.

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Hadoop: Hadoop is an open source framework for processing, storing and analyzing massive amounts of distributed unstructured data. Originally created by Doug Cutting at Yahoo!, Hadoop was inspired by MapReduce, a user-defined function developed by Google in early 2000s for indexing the Web. It was designed to handle petabytes and exabytes of data distributed over multiple nodes in parallel.

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BigData onDemand Training for :
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Big Data Training for FastTrack Session!
 5 Days Classroom Training on - 29th March 2014 to 2nd April 2014

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