• DocumentCode
    228432
  • Title

    Big data implementation and visualization

  • Author

    Gupta, Deepika ; Siddiqui, Sameera

  • Author_Institution
    Amity Inst. of Inf. Technol., Noida, India
  • fYear
    2014
  • fDate
    1-2 Aug. 2014
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    Government agencies and large corporations are launching research programs to address big data´s challenges. Visualization in today´s time is very effective for presenting essential information in vast amounts of data. Big-data discovery tools present new research opportunities to the graphics and visualization community. The size of the collected data about the Web and mobile device users is even greater. To provide the ability to make sense and maximize utilization of such vast amounts of data for knowledge discovery and decision making is crucial to scientific advancement; we need new tools beyond conventional data mining and statistical analysis. Visualization is a tool which is shown to be effective for gleaning insight in big data. Here we also discuss data cube that fits in a tablet or a smart phone memory, actually for billions of entrances; we call this information structure a nanocube. [13]. We present pseudo code to compute and query a nanocube [13], and show how it can be used to generate well-known visual encodings such as heat maps, histograms, and parallel coordinate plots. While Apache* Hadoop* and other technologies are emerging to support back-end concerns such as storage and processing, visualization-based data discovery tools focus on the front end of big data-on helping businesses explore the data more easily and understand it more fully.
  • Keywords
    Big Data; data mining; data visualisation; public domain software; query processing; statistical analysis; Apache* Hadoop*; Big-Data discovery tools; data cube; data mining; decision making; government agencies; graphics community; information structure; knowledge discovery; nanocube query; pseudocode; smart phone memory; statistical analysis; tablet; visual encodings; visualization community; visualization-based data discovery tools; Big data; Business; Conferences; Data visualization; Real-time systems; Servers; Visualization; Analytics; Apache Hadoop; Visualization; data cubes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Engineering and Technology Research (ICAETR), 2014 International Conference on
  • Conference_Location
    Unnao
  • ISSN
    2347-9337
  • Type

    conf

  • DOI
    10.1109/ICAETR.2014.7012883
  • Filename
    7012883