Closing the Gap between Data Availability and Insight
While data volumes are growing by leaps and bounds, firms are only analyzing 12% of the data that is being captured and stored, according to a recent Forrester survey. Several reasons for this shortfall were given by survey respondents:
� The inflexibility of their existing BI tools to handle the volume, velocity and disparate formats of Big Data
� Enterprise and externally sourced data changes faster than organizations can process into actionable insights
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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Big Data Training for FastTrack Session on Apr 5th To 9th 2014