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Evaluation Of Intuitive Platforms For Data Analytics

Authors: Panova, Denitsa Ivova; Martin Marquez, Manuel; Romero Marin, Antonio;

Evaluation Of Intuitive Platforms For Data Analytics

Abstract

Abstract Nowadays the world is over flooded with information. With the rise of Big Data, huge amounts of information, diverging in their variety, velocity and volume, a new data analytics branch has developed. It has emerged from the need to offer to the researchers an easier way, an intuitive software with which to analyze the accumulated pile of information. The purpose of this project is to investigate some of these data analytics platforms and evaluate them for the unique requirements of CERN environment and use cases. The question which needs to be answered is - are those platforms able to facilitate the users to conduct analysis without the necessity to acquire new skill set. Initial point of the report is to give context of the project and to specify why the use of Big Data technologies is required at CERN. Additionally, it gives an overview of the Big Data tools which are used in the evaluated platforms. The core of the report consists of the mechanism behind each of three data analytics platforms and their evaluation in terms of their merits and downsides.

Keywords

CERN openlab summer student

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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