ABSTRACT
Effective data analysis to improve any asset’s performance has always been a part of a competitive business. Conventional decision making processes based on traditional data management are gradually being replaced by the demand of “ad hoc” queries that are responded to quickly and proactively. These rely on actionable information provided by sophisticated analytical tools using real-time online business performance data. In order to achieve real-time business intelligence, smarter analytical tools and technologies such as Expert Systems (ES) are needed. With advancement in data acquisition and storage capabilities, a large amount of data is now available from different operational units. The requirement is to extract useful knowledge from qualitative and/or quantitative data in order to provide additional information to system experts and operators. According to Herschel and Jones (2005) Knowledge Management (KM) within complex assets involves the systematic process of finding, selecting, organizing and presenting information in a way to improve employees’ comprehension in a specific area of interest. Whereas, Business Intelligence (BI) is a set of all technologies, applications and means of collecting, integrating and presenting business data to improve decision making. Today’s need is to integrate KM and BI in order to achieve a higher level of efficiency within different business units. Briefly speaking, KM is an integral part of BI and their effective integration has been emphasized in the past years (for instance see Hamilia 2001, Hameed 2004).
