Visualization of Big Data with the Map-Reduce program execution platform: Hadoop
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2017 by IJETT Journal | ||
| Volume-54 Number-2 |
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| Year of Publication : 2017 | ||
| Authors : Sara Riahi, Azzeddine Riahi |
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| DOI : 10.14445/22315381/IJETT-V54P214 |
Citation
1 Sara Riahi, 2 Azzeddine Riahi "Visualization of Big Data with the Map-Reduce program execution platform: Hadoop", International Journal of Engineering Trends and Technology (IJETT), V54(2),94-104 December 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
"Big data" is the fashionable term currently found in all professional conferences related to data science, predictive modeling, data mining, to name just a few areas literally electrified by the prospect of integrating larger datasets and data flows more quickly into their business processes and other organizational processes. As is often the case when new technologies begin to transform industries, new terminologies emerge, along with new approaches to conceptualize reality, solve problems, or improve processes. A few years ago, we limited ourselves to "segment" customers into groups that could acquire specific properties or services. It is now possible and common to build models for each customer in real time as they browse the Internet for specific properties: Instantly, prospects` interests are analyzed and it is possible to display highly targeted advertising, which is a level of personalization inconceivable only a few years ago. Inevitably, the disappointment may be up to expectations in many areas as technology around big data are promising. A limited number of data accurately describing a critical aspect of reality (vital to the business) is far more valuable than a deluge of data on less essential aspects of that reality. The purpose of this article is to clarify and highlight some interesting opportunities around big data, and illustrate how analytic platforms can leverage this wealth of data to optimize a process, solve problems, or improve customer knowledge.
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Keywords
Massive data, Analytics, Hadoop, HDFS, Map Reduce