Big Data Training for Next Generation Data Scientists

Amazon continued and Google kicked off increasingly aggressive moves into the Big Data market. Each introduced new products and services to allow enterprises to leverage Big Data analytics and storage-as-a-service with the usual benefits associated with public Cloud services (elasticity, pay-by-the-drink, trading upfront CAPEX for monthly OPEX, etc.) Specifically, Amazon introduced RedShift, an analytic-database-as-a-service, to its portfolio and struck a deal with MapR to allow customers to run its Hadoop distribution on Amazon Web Service, among other announcements. Amazon also continued to build its Elastic MapReduce business. Google finally got into the Big Data game by productizing Big Data tools and technologies, such as BigQuery, it has long used internally, and likewise introduced MapR as a service via Google Compute Engine.

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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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.

Big Data / Hadoop Training Online
Online Batch Big Data / Hadoop Training
Big Data / Hadoop Training
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weekends(Classroom) - 4th Jan 2014
Fast Track (Classroom) -6th Jan 2014
Online Class- 6th Jan 2014