Big Data using Hadoop Analytics

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Mind Map on Big Data using Hadoop Analytics, created by jebashanthi293 on 01/01/2014.
jebashanthi293
Mind Map by jebashanthi293, updated more than 1 year ago
jebashanthi293
Created by jebashanthi293 over 11 years ago
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Resource summary

Big Data using Hadoop Analytics
  1. Definion

    Annotations:

    • 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.   
    1. Hadoop

      Annotations:

      • 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.   
      1. Problem-solving with Hadoop

        Annotations:

        • 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.   
        1. Big data and cloud computing
          1. Hadoop Analytics

            Annotations:

            • 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. capabilities for Hadoop Analytics
              1. Fastest Platform to build analytics

                Annotations:

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

                  Annotations:

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

                    Annotations:

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

                    Annotations:

                    • 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. Big data in Private sectors
                      1. Ebay

                        Annotations:

                        • 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
                        1. FaceBook

                          Annotations:

                          • Facebook handles 50 billion photos from its user base.
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