The main benefit of Hadoop is that it allows enterprises to process and analyze large volumes of unstructured and semi-structured data, heretofore inaccessible to them, in a cost- and time-effective manner. Because Hadoop clusters can scale to petabytes and even exabytes of data
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.
In a recent survey, 46% of Big Data practitioners report that they have only realized partial value from their Big Data deployments. An unfortunate 2% declared their Big Data deployments total failures, with no value achieved.
The three compelling reasons for this struggle to achieve maximum business value form Big Data are:
� A lack of skilled Big Data practitioners.
� �Raw� and relatively immature technology.
� A lack of compelling business use case.
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