Despite the benefits of investing in Big Data systems are largely recognised, their adoption have been slower than expected. Actually, organisations and companies cannot migrate their systems to new a technological infrastructure without a safe integration to their legacy systems and data. For these reasons, it is required to evolve Big Data technologies with mature functions for supporting portability, interoperability and reusability. This paper illustrates a practical use case exploiting the Model-driven capabilities of the TOREADOR platform as a way to fast track the uptake of business-driven Big Data models.
Facing big data variety in a model driven approach / M. Leida, C. Ruiz, P. Ceravolo - In: Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), 2016 IEEE 2nd International Forum on[s.l] : IEEE, 2016. - ISBN 9781509011315. - pp. 1-6 (( Intervento presentato al 2. convegno RTSI tenutosi a Bologna nel 2016 [10.1109/RTSI.2016.7740641].
Facing big data variety in a model driven approach
P. Ceravolo
2016
Abstract
Despite the benefits of investing in Big Data systems are largely recognised, their adoption have been slower than expected. Actually, organisations and companies cannot migrate their systems to new a technological infrastructure without a safe integration to their legacy systems and data. For these reasons, it is required to evolve Big Data technologies with mature functions for supporting portability, interoperability and reusability. This paper illustrates a practical use case exploiting the Model-driven capabilities of the TOREADOR platform as a way to fast track the uptake of business-driven Big Data models.File | Dimensione | Formato | |
---|---|---|---|
ceravolo.pdf
accesso riservato
Tipologia:
Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione
250.64 kB
Formato
Adobe PDF
|
250.64 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.