Big Data using Hadoop Analytics

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• Big data refers to the size of a dataset that has grown too large to be manipulated through traditional methods. These methods include capture, storage, and processing of the data in a tolerable amount of time. Although the term big data was once applied to the concept of data warehouses, it now refers to large-scale processing architectures that focus on capacity, throughput, and genericity of processing.   

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• Hadoop refers to the specific software framework developed under the Apache Project for massively distributed data processing. Its design supports a highly scalable network of thousands of nodes backed by petabytes of data. Hadoop was originally designed using the Java™ language but today has extended itself to many other languages for scripting. Understand the architectures possible with Hadoop and the benefits of their use.   

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• Hadoop was inspired by Google's MapReduce usage model, Hadoop is a generic application framework for the processing of massive amounts of data. Learn about the use of Hadoop in artificial intelligence with Apache Mahout, Hadoop with Java technology, and combining Hadoop with the Dojo toolkit for data visualization.   

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• Hadoop is at the core of the Big Data revolution. Vendors such as Cloudera, MapR, and Hortonworks have taken this open source software that enables distributed parallel processing of huge amounts of data, and included important data management and support capabilities.

1. Fastest Platform to build analytics

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   • Sophisticated but accessible predictive and spatial tools, combined in a simple, workflow design environment
2. Simple sharing of Big Data analytics

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   • Single click sharing of analytic applications that can be used by any decision maker
3. All relevant data

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   • Access, integration, and cleaning of sources of data as varied as Hadoop (including Cloudera & MapR) or NoSQL (MongoDB) and Excel or Teradata

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• Apache Hadoop software is the only distribution built from silicon up to enable the widest range of data analysis on Apache Hadoop. It is the first with hardware-enhanced performance and security capabilities

1. Ebay

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   • Ebay.com  uses two data warehouses at 7.5 petabytes and 40PB as well as a 40PB Hadoop cluster for search, consumer recommendations, and merchandising
2. FaceBook

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   • Facebook handles 50 billion photos from its user base.