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Big Data Analytic Approaches Classification

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Date
2017
Dewey
Programmation, logiciels, organisation des données
Sujet
Big Data Analytic; Analytic Models for Big Data; Analytical Data Management Applications
DOI
http://dx.doi.org/10.5220/0006437801510162
Conference name
12th International Conference on Software Technologies (ICSOFT 2017)
Conference date
07-2017
Conference city
Madrid
Conference country
Spain
Book title
Proceedings of the 12th International Conference on Software Technologies 2017
Author
Cardoso, Jorge; Maciaszek, Leszek; van Sinderen, Marten; Cabello, Enrique
Publisher
SciTePress
Publisher city
Setúbal
Year
2017
Pages number
487
ISBN
978-989-758-262-2
URI
https://basepub.dauphine.fr/handle/123456789/18635
Collections
  • LAMSADE : Publications
Metadata
Show full item record
Author
Cardinale, Yudith
100644 Universidad Simon Bolivar [USB]
Guehis, Sonia
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rukoz, Marta
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Type
Communication / Conférence
Item number of pages
151-162
Abstract (EN)
Analytical data management applications, affected by the explosion of the amount of generated data in the context of Big Data, are shifting away their analytical databases towards a vast landscape of architectural solutions combining storage techniques, programming models, languages, and tools. To support users in the hard task of deciding which Big Data solution is the most appropriate according to their specific requirements, we propose a generic architecture to classify analytical approaches. We also establish a classification of the existing query languages, based on the facilities provided to access the Big Data architectures. Moreover, to evaluate different solutions, we propose a set of criteria of comparison, such as OLAP support, scalability, and fault tolerance support. We classify different existing Big Data analytics solutions according to our proposed generic architecture and qualitatively evaluate them in terms of the criteria of comparison. We illustrate howour proposed generic architecture can be used to decide which Big Data analytic approach is suitable in the context of several use cases.

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