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DOI: 10.14569/IJACSA.2016.070337
PDF

Extract Five Categories CPIVW from the 9V’s Characteristics of the Big Data

Author 1: Suhail Sami Owais
Author 2: Nada Sael Hussein

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: There is an exponential growth in the amount of data from different fields around the world, and this is known as Big Data. It needs more data management, analysis, and accessibility. This leads to an increase in the number of systems around the world that will manage and manipulate the data in different places at any time. Big Data is a systematically analysed data that depends on the existence of complex processes, devices, and resources. Data are no longer stored in traditional database storage types or on such forms like database, which only on structured data are limited, but surpassed them to the unstructured or semi-structured data. Thus, Big Data has several characteristics and specific properties proportionate with the size of the data with the enormous and rapid development in all business and areas of life. In this work, we study the relationship between the characteristics of Big Data and extract some categories from them. From this, we conclude that there are five categories, and these categories are related to each other.

Keywords: Big Data; Characteristics; Categories; Management; Analysis; Anywhere and Anytime

Suhail Sami Owais and Nada Sael Hussein, “Extract Five Categories CPIVW from the 9V’s Characteristics of the Big Data” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070337

@article{Owais2016,
title = {Extract Five Categories CPIVW from the 9V’s Characteristics of the Big Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070337},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070337},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Suhail Sami Owais and Nada Sael Hussein}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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