Aggregation and multidimensional analysis are well-known powerful tools for extracting useful knowledge, shaped in a summarized manner, which are being successfully applied to the annoying problem of managing and mining big data produced by large-scale scientific applications. Indeed, in the context of big data analytics, aggregation approaches allow us to provide meaningful descriptions of these data, otherwise impossible for alternative data-intensive analysis tools. On the other hand, multidimensional analysis methodologies introduce fortunate metaphors that significantly empathize the knowledge discovery phase from such huge amounts of data. Following this main trend, several big data aggregation and multidimensional analysis approaches have been proposed recently. The goal of this paper is to (i) provide a comprehensive overview of state-of-the-art techniques and (ii) depict open research challenges and future directions adhering to the reference scientific field.

Aggregation and multidimensional analysis of big data for large-scale scientific applications: Models, issues, analytics, and beyond

CUZZOCREA, Alfredo Massimiliano
2015

Abstract

Aggregation and multidimensional analysis are well-known powerful tools for extracting useful knowledge, shaped in a summarized manner, which are being successfully applied to the annoying problem of managing and mining big data produced by large-scale scientific applications. Indeed, in the context of big data analytics, aggregation approaches allow us to provide meaningful descriptions of these data, otherwise impossible for alternative data-intensive analysis tools. On the other hand, multidimensional analysis methodologies introduce fortunate metaphors that significantly empathize the knowledge discovery phase from such huge amounts of data. Following this main trend, several big data aggregation and multidimensional analysis approaches have been proposed recently. The goal of this paper is to (i) provide a comprehensive overview of state-of-the-art techniques and (ii) depict open research challenges and future directions adhering to the reference scientific field.
9781450337090
http://dl.acm.org/citation.cfm?id=2791377&CFID=865033415&CFTOKEN=60432567
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2872494
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 10
social impact