Towards Automation of Business Intelligence Services Using Hybrid Intelligent System Approach

Abstract

Business Intelligence (BI) includes many tools, techniques and technologies. BI processes often involve team of human decision makers and end-users to extract, explore and analyse the data. The results, decisions or models after analysis need to be implemented into operational systems. There can be considerable time delay between business events happening and action taken thus loosing opportunities. Intelligent techniques such as rule-based reasoning and case-based reasoning have been used extensively to address wide range of intelligent tasks including personalisation and recommendation. Some BI tasks can be modelled, automated and delivered through services rather than done on ad-hoc basis. The authors represent a service based approach to BI where a service corresponds to a well defined analytical functionality implemented using intelligent technique(s), filtering techniques or hybrids of them accessing only relevant data from database specifically modelled and designed for such tasks. The authors discuss an application of the approach for a value-added service in mobile domain.

Impact of Organizational Characteristics on Business Intelligence Practices in Selected Indian Banks

“…Ferguson (2009) suggested in his paper that unreliable data can impact every part of a retail banking business as banks are moving towards customer level risk management, customer based pricing and cross selling of profitable products and services to drive up revenue streams. Sonar (2006) proposed a hybrid business intelligence system for retail banking to involve analysis of lot of data with different perspectives. Retail banking needs better analysis and understanding of customers, products and transaction.…”