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PInCom project: SaaS Big Data Platform for and Communication Channels
dc.contributor.author | Lombardo, Juan Manuel | |
dc.contributor.author | López, Miguel Ángel | |
dc.contributor.author | Mirón, Felipe | |
dc.contributor.author | Velasco, Susana | |
dc.contributor.author | Sevilla, Juan Pablo | |
dc.contributor.author | Mellado, Juan | |
dc.date | 2016 | |
dc.date.accessioned | 2020-06-24T08:30:00Z | |
dc.date.available | 2020-06-24T08:30:00Z | |
dc.identifier.issn | 1989-1660 | |
dc.identifier.uri | https://reunir.unir.net/handle/123456789/10208 | |
dc.description.abstract | The problem of optimization will be addressed in this article, based on the premise that the successful implementation of Big Data solutions requires as a determining factor not only effective -it is assumed- but the efficiency of the responsiveness of management information get the best value offered by the digital and technological environment for gaining knowledge. In adopting Big Data strategies should be identified storage technologies and appropriate extraction to enable professionals and companies from different sectors to realize the full potential of the data. A success story is the solution PInCom: Intelligent-Communications Platform that aims customer loyalty by sending multimedia communications across heterogeneous transmission channels. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI) | es_ES |
dc.relation.ispartofseries | ;vol. 3, nº 6 | |
dc.relation.uri | https://www.ijimai.org/journal/bibcite/reference/2532 | es_ES |
dc.rights | openAccess | es_ES |
dc.subject | data mining | es_ES |
dc.subject | optimization | es_ES |
dc.subject | relational values | es_ES |
dc.subject | big data | es_ES |
dc.subject | analytics | es_ES |
dc.subject | NoSQL | es_ES |
dc.subject | IJIMAI | es_ES |
dc.title | PInCom project: SaaS Big Data Platform for and Communication Channels | es_ES |
dc.type | article | es_ES |
reunir.tag | ~IJIMAI | es_ES |
dc.identifier.doi | https://doi.org/10.9781/ijimai.2016.362 |