A Perspective on Data Mining Integration with Business Intelligence

Abstract

Business Intelligence (BI) is an emergent area of the Decision Support Systems (DSS) discipline. Over the past years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. The purpose of this chapter is to discuss the relevance of DM integration with BI, and its importance to business users. From the literature review, it was observed that the definition of an underlying structure for BI is missing, and therefore a framework is presented. It was also observed that some efforts are being done that seek the establishment of standards in the DM field, both by academics and by people in the industry. Supported by those findings, this chapter introduces an architecture that can conduct to an effective usage of DM in BI. This architecture includes a DM language that is iterative and interactive in nature. This chapter suggests that the effective usage of DM in BI can be achieved by making DM models accessible to business users, through the use of the presented DM language.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts

“…We tried to take these cases into account by constructing a RegEx that matches the typical way of listing references (e.g. [ 1 ] Westergaard, …). Such a pattern can be matched by the RegEx “^\[\d+\]\s[A-Za-z]”.…”

“…Text mining has become a widespread approach to identify and extract information from unstructured text. Text mining is used to extract facts and relationships in a structured form that can be used to annotate specialized databases, to transfer knowledge between domains and more generally within business intelligence to support operational and strategic decision-making [ 1 – 3 ]. Biomedical text mining is concerned with the extraction of information regarding biological entities, such as genes and proteins, phenotypes, or even more broadly biological pathways (reviewed extensively in [ 3 – 9 ]) from sources like scientific literature, electronic patient records, and most recently patents [ 10 – 13 ].…”

Design of a remote assistance model for truck maintenance in the mining industry

“…Both specify the tasks to be performed in each phase described by the process, assigning specific tasks and defining what is desirable to obtain after each phase. However, studies such as (Azevedo and Santos, 2008) have shown that, although clear parallels can be drawn between them, CRISP-DM is complete because it takes into account the application to the business environment of the results.…”

Aplicación de los árboles de decisión en la identificación de patrones de lesiones fatales por causa externa en el municipio de Pasto, Colombia

“…Ambas especifican las tareas a realizar en cada fase descrita por el proceso, asignando tareas concretas y definiendo lo que es deseable obtener tras cada fase. Azevedo y Santos (14) comparan ambas implementaciones y llegan a la conclusión de que, aunque se puede establecer un paralelismo claro entre ellas, CRISP-DM es más completo porque tiene en cuenta la aplicación al entorno de negocio de los resultados, y por ello es la que se adoptó popularmente. En encuestas realizadas en KDNuggets en 2002, 2004, 2007 y 2014 se comprobó que CRISP-DM era la principal metodología utilizada, cuatro veces más que SEMMA (14) .…”

“…Azevedo y Santos (14) comparan ambas implementaciones y llegan a la conclusión de que, aunque se puede establecer un paralelismo claro entre ellas, CRISP-DM es más completo porque tiene en cuenta la aplicación al entorno de negocio de los resultados, y por ello es la que se adoptó popularmente. En encuestas realizadas en KDNuggets en 2002, 2004, 2007 y 2014 se comprobó que CRISP-DM era la principal metodología utilizada, cuatro veces más que SEMMA (14) . La metodología CRISP-DM para proyectos de minería de datos no es la "más actual" o "la mejor", pero es muy útil para comprender esta tecnología o extraer ideas para diseñar o revisar métodos de trabajo para proyectos de similares características.…”