ABSTRACT
Cognitive decision-making is an intellectual process aimed at the selection of a course of action among various choices. Information technology applications that support decision-making processes had an evolutionary transformation of spreadsheet software to the complex decision-support systems. The cognitive process of decision-making is being practiced through various intelligent information systems. The intelligent decision support system is being used by decision makers to make smart decisions in real-time dynamic environment based on intelligent data. To achieve intelligent data, it is needed to transform existing relational data and big data into agent-oriented data and subsequent design of data model to be in tune to the intelligent decision support system. For such system, the intelligent database agent (IDA) is designed to generate the analytical data for cognitive decision-making. The intelligent database agent is based on predictive data analytics. In any organization, predictive models utilize the sample which is found in historical and real-time transactional data to identify threats and prospects. IDA confines associations between many aspects to permit evaluation of threat or prospective associated with a particular set of conditions, steering cognitive decision-making. The development phases for the intelligent database agent is demonstrated and implemented to retrieve 64the information for cognitive decision-making in the proposed framework. The proposed framework is evaluated based on the complexity of verities of data, data query complexity, i-DSS query Execution Time, memory block used, volume of data, level of aggregation, reusability, flexibility, scalability and manageability are taken into the consideration for justification.
