Among the various interpretations and meanings of the well-known Vs (Volume, Velocity, Variety) of Big Data, V as Value represents the most significant and critical innovation for enterprises, which are a well-known case of digital ecosystems. The key issue for big enterprise data consists in extracting knowledge for creating new value and innovation for the target enterprise. Therefore, the big data analytics phase plays a critical role to this end. Following these considerations, in this paper we provide the following three contributions: (i) an overview of most relevant proposals in the context of big data innovation for enterprises; (ii) a reference architecture for supporting advanced big data analytics over big enterprise data; (iii) a discussion on future challenges in the context of big data innovation for enterprises. 1.

Big-data-driven innovation for enterprises: Innovative big value paradigms for next-generation digital ecosystems

Loia V.;Tommasetti A.
2017

Abstract

Among the various interpretations and meanings of the well-known Vs (Volume, Velocity, Variety) of Big Data, V as Value represents the most significant and critical innovation for enterprises, which are a well-known case of digital ecosystems. The key issue for big enterprise data consists in extracting knowledge for creating new value and innovation for the target enterprise. Therefore, the big data analytics phase plays a critical role to this end. Following these considerations, in this paper we provide the following three contributions: (i) an overview of most relevant proposals in the context of big data innovation for enterprises; (ii) a reference architecture for supporting advanced big data analytics over big enterprise data; (iii) a discussion on future challenges in the context of big data innovation for enterprises. 1.
9781450352253
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4759113
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