Business lntelligence (Bl) applied inData Analytics (DA) to generate key information to support business decision making, has been an important area for more than two decades. In the last years, the trend of Big Data (BD) has emerged and became a core element of Business lntelligence research, showing that support, as this showed in this work, may represent a huge help for areas with competitiveness problems. The paper aims to present the idea of creating a dialogue between companies with a low level of digitalization and institutions, creating a I4.O Readiness Model service provided by regional institutions to companies. The service, called I4.0 GRADE, creates a rank of the 4.0 technology level present in the company and its digitization level, surpassing the classic survey standard that is currently used in the creation of services of this type. This autonomous and independent process can be a fundamental help for companies, and it is done by using two approaches, one based on the reflections extrapolated from dependency structures such as the Bayesian Networks, and other excluding the "privileged" interdependence of some variables, proposing a mutual and complete influence.

Oualità del servizio e big data in I4.0 Grade Model: un'applicazione di rete bayesiana.

Paolo Carmelo Cozzucoli;
2021

Abstract

Business lntelligence (Bl) applied inData Analytics (DA) to generate key information to support business decision making, has been an important area for more than two decades. In the last years, the trend of Big Data (BD) has emerged and became a core element of Business lntelligence research, showing that support, as this showed in this work, may represent a huge help for areas with competitiveness problems. The paper aims to present the idea of creating a dialogue between companies with a low level of digitalization and institutions, creating a I4.O Readiness Model service provided by regional institutions to companies. The service, called I4.0 GRADE, creates a rank of the 4.0 technology level present in the company and its digitization level, surpassing the classic survey standard that is currently used in the creation of services of this type. This autonomous and independent process can be a fundamental help for companies, and it is done by using two approaches, one based on the reflections extrapolated from dependency structures such as the Bayesian Networks, and other excluding the "privileged" interdependence of some variables, proposing a mutual and complete influence.
Big Data; Digitalization; Bayesian Network; Business lntelligence; I4.0 Readiness Model; B2G2B
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/332477
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