Fiche du document
22 novembre 2017
- handle: 10670/1.l9ceav
- hal: hal-01765243
- doi: 10.1007/978-3-319-70241-4_12
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-70241-4_12
http://creativecommons.org/licenses/by/ , info:eu-repo/semantics/OpenAccess
Sujets proches
Modelmaking Modelling Model-making Molding (Clay, plaster, etc.) Clay modeling ModellingCiter ce document
Azadeh Nasiri et al., « From Indicators to Predictive Analytics: A Conceptual Modelling Framework », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10.1007/978-3-319-70241-4_12
Métriques
Partage / Export
Résumé
Predictive analytics provides organisations with insights about future outcomes. Despite the hype around it, not many organizations are using it. Organisations still rely on the descriptive insights provided by the traditional business intelligence (BI) solutions. The barriers to adopt predictive analytics solutions are that businesses struggle to understand how such analytics could enhance their existing BI capabilities, and also businesses lack a clear understanding of how to systematically design the predictive analytics. This paper presents a conceptual modelling framework to overcome these barriers. The framework consists of two modelling components and a set of analysis that systematically (1) justify the needs for predictive analytics within the organisational context, and (2) identify the predictive analytics design requirements. The framework is illustrated using a real case adopted from the literature.