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Big Data

The well-known three Vs of Big Data - Volume, Variety, and Velocity – are increasingly placing pressure on organizations that need to manage this data as well as extract value from this data deluge for Predictive Analytics and Decision-Making. Big Data technologies, services, and tools such as Hadoop, MapReduce, Hive and NoSQL/NewSQL databases and Data Integration techniques, In-Memory approaches, and Cloud technologies have emerged to help meet the challenges posed by the flood of Web, Social Media, Internet of Things (IoT) and machine-to-machine (M2M) data flowing into organizations.



Big Data Articles

RainStor, a provider of big data management software, has unveiled the RainStor Big Data Analytics on Hadoop, which the company describes as the first enterprise database running natively on Hadoop. It is intended to enable faster analytics on multi-structured data without the need to move data out of the Hadoop Distributed File System (HDFS) environment. There is architectural compatibility with the way Rainstor manages data and the way Hadoop Distributed File Systems manage CSV files, says Deirdre Mahon, vice president of marketing at Rainstor.

Posted January 25, 2012

The Oracle Big Data Appliance, an engineered system of hardware and software that was first unveiled at Oracle OpenWorld in October, is now generally available. The new system incorporates Cloudera's Distribution Including Apache Hadoop (CDH3) with Cloudera Manager 3.7, plus an open source distribution of R. The Oracle Big Data Appliance represents "two industry leaders coming together to wrap their arms around all things big data," says Cloudera COO Kirk Dunn.

Posted January 25, 2012

"Big data" and analytics have become the rage within the executive suite. The promise is immense - harness all the available information within the enterprise, regardless of data model or source, and mine it for insights that can't be seen any other way. In short, senior managers become more effective at business planning, spotting emerging trends and opportunities and anticipating crises because they have the means to see both the metaphorical trees and the forest at the same time. However, big data technologies don't come without a cost.

Posted January 11, 2012

The big data playing field grew larger with the formation of Hortonworks and HPCC Systems. Hortonworks is a new company consisting of key architects and core contributors to the Apache Hadoop technology pioneered by Yahoo. In addition, HPCC Systems, which has been launched by LexisNexis Risk Solutions, aims to offer a high performance computing cluster technology as an alternative to Hadoop.

Posted July 27, 2011

The rise of "big data" solutions - often involving the increasingly common Hadoop platform - together with the growing use of sophisticated analytics to drive business value - such as collective intelligence and predictive analytics - has led to a new category of IT professional: the data scientist.

Posted May 12, 2011

Google's first "secret sauce" for web search was the innovative PageRank link analysis algorithm which successfully identifies the most relevant pages matching a search term. Google's superior search results were a huge factor in their early success. However, Google could never have achieved their current market dominance without an ability to reliably and quickly return those results. From the beginning, Google needed to handle volumes of data that exceeded the capabilities of existing commercial technologies. Instead, Google leveraged clusters of inexpensive commodity hardware, and created their own software frameworks to sift and index the data. Over time, these techniques evolved into the MapReduce algorithm. MapReduce allows data stored on a distributed file system - such as the Google File System (GFS) - to be processed in parallel by hundreds of thousands of inexpensive computers. Using MapReduce, Google is able to process more than a petabyte (one million GB) of new web data every hour.

Posted January 11, 2010

Google introduced the MapReduce algorithm to perform massively parallel processing of very large data sets using clusters of commodity hardware. MapReduce is a core Google technology and key to maintaining Google's website indexes.

Posted September 14, 2009

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