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Hadoop is an Apache open source project that provides a parallel storage and processing framework. Its primary purpose is to run MapReduce batch programs in parallel on tens to thousands of server nodes.
Hadoop scales out to large clusters of servers and storage using the Hadoop Distributed File System (HDFS) to manage huge data sets and spread them across the servers.
One of Hadoop?s greatest benefits is the ability of programmers to write application modules in almost any language and run them in parallel on the same cluster that stores the data. This is a profound change! With Hadoop, any programmer can harness the power and capacity of thousands of CPUs and hard drives simultaneously.
More advantages of Hadoop include affordability (it runs on commodity hardware), open source (free download from Cloudera), and agility (store any data, run any analysis).
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.
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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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