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
Enterprise practitioners believe the potential value of Big Data is significant, but many are struggling to derive maximum value from their investments in related technology. While a majority a Fortune 500 companies have Big Data deployments in production, and a significant percentage of mid-sized enterprises have proof-of-concept and pilot projects underway, We estimate that close to half have not realized the level of value anticipated at their onset.
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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Big Data Training for FastTrack Session on Mar 29- Apr 2, 2014