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EnglishOLAPing and Mining Big Data is among one of the most attracting research contexts of recent years. Essentially, this puts emphasis on how classical OLAPing and Mining algorithms can be extended in order to deal with novel features of Big Data, such as volume, variety and velocity. This novel challenge opens the door to a widespread number of challenging research problems that will generate both academic and industrial spin-offs in future years. Following this main trend, in this paper we provide a brief discussion on most relevant open problems and future directions on the fundamental issue of OLAPing and Mining Big Data.
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| Titolo: | OLAPing and Mining Big Data: Large-Scale, Long-Running, Serendipitous Computations within Next-Generation Clouds | |
| Autori: | ||
| Data di pubblicazione: | 2014 | |
| Abstract: | OLAPing and Mining Big Data is among one of the most attracting research contexts of recent years. Essentially, this puts emphasis on how classical OLAPing and Mining algorithms can be extended in order to deal with novel features of Big Data, such as volume, variety and velocity. This novel challenge opens the door to a widespread number of challenging research problems that will generate both academic and industrial spin-offs in future years. Following this main trend, in this paper we provide a brief discussion on most relevant open problems and future directions on the fundamental issue of OLAPing and Mining Big Data. | |
| Handle: | http://hdl.handle.net/20.500.11770/312740 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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