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Trends of Big Data Analytics Practices

Big data analytics

  • Big data analytics is the process of examining large data sets containing various of data types to uncover hidden patterns, unknown correlations and other useful business insights
  • The sources for the large data sets includes server logs, social media, mobile devices and sensors. These data’s are of unstructured and semi-structured type.
  • The traditional databases and Relational databases will not fit these unstructured and semi-structured data obtained from data sources
  • This makes an necessity for the move to the new technology of <b>Hadoop</b>.
  • Hadoop is an framework that supports the processing of huge and diversed data sets across clustered systems
  • Hadoop> does with support of related tools like YARN, MapReduce, Hive…
  • This serves as an central repository for all incoming streams of raw data.
  • Hadoop is not a single product instead its an collection of components.
  • Its popularity is in storing, analyzing and in fast retrieval of unstructured data in low cost effective manner.

Data As A Service [DaaS]

  • Data as a service (DaaS) is the delivery of statistical analysis tools or information obtained from large information sets in order to gain a competitive advantage for an organization.
  • This is done over the immense volume of unstructured data that was updated in the regular basis


– the data’s obtained using web crawlers are sent into framework of Hadoop for the following processing

  • Data Storage
  • Data Processing
  • Data Management

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