Authors:
Alfredo Cuzzocrea
1
;
2
;
Carmine Gallo
2
and
Marco Mastratisi
3
Affiliations:
1
Department of Computer Science, University of Paris City, Paris, France
;
2
IDEA Lab, University of Calabria, Rende, Italy
;
3
SMARTCHAIN – ICT Technologies, Crotone, Italy
Keyword(s):
Big Data, Big Data Analytics, Multidimensional Machine Learning, Cloud-Enabled Big Data Infrastructures.
Abstract:
Multidimensional Machine Learning is emerging as one of the key features in the whole Big Data Analytics landscape. Within this broad context, the OLAP paradigm is a reference pillar, and it represents the theoretical and methodological foundation of the so-called Multidimensional Big Data Analytics trend, an emerging trend in the Big Data era. In this paper, we show how the state-of-the-art ClustCube framework, which predicates the marriage between OLAP and Clustering methodologies, can be successfully used and exploited for effectively and efficiently supporting Multidimensional Big Data Analytics in real-life big data applications and systems.