Hadoop, NoSQL and massively parallel analytic databases are not mutually exclusive. Far from it, we believe the three approaches are complimentary to each other and can and should co-exist in many enterprises. Hadoop excels at processing and analyzing large volumes of distributed, unstructured data in batch fashion for historical analysis. NoSQL databases are adept at storing and serving up multi-structured data in near-real time for web-based Big Data applications. And massively parallel analytic databases are best at providing near real-time analysis of large volumes of mainly structured data.
Providing effective business analytics tools and technologies to the enterprise is a top priority of CIOs and for good reason. Effective business analytics � from basic reporting to advanced data mining and predictive analytics � allows data analysts and business users alike to extract insights from corporate data that, when translated into action, deliver higher levels of efficiency and profitability to the enterprise.
ise 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.
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Big Data Training for FastTrack Session!
5 Days Classroom Training on - 1st March 2014 to 5th March 2014