AHP Model for the Big Data Analytics Platform Selection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F15%3A39899974" target="_blank" >RIV/00216275:25410/15:39899974 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

AHP Model for the Big Data Analytics Platform Selection

Original language description

Big data analytics refers to a set of advanced technologies, which are designed to efficiently operate and maintain data that are not only big, but also high in variety and velocity. This paper analyses these emerging big data technologies and presents acomparison of the selected big data analytics platforms through the whole data life. The main aim is then to propose and demonstrate the use of an AHP model for the big data analytics platform selection, which may be used by businesses, public sector institutions as well as citizens to solve multiple criteria decision-making problems. It would help them to discover patterns, relationships and useful information in their big data, make sense of them and to take responsive action.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

AE - Management, administration and clerical work

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Acta Informatica Pragensia

ISSN

1805-4951

e-ISSN

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Volume of the periodical

4

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

14

Pages from-to

108-121

UT code for WoS article

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EID of the result in the Scopus database

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