Intelligent data analysis - support for development of SMEs sector

The paper studies possibilities of intelligent data analysis application for discovering knowledge hidden in small and medium-sized enterprises’ (SMEs) data, on the territory of the province of Vojvodina. The knowledge revealed by intelligent analysis, and not accessible by any other means, could be the valuable starting point for working out of proactive and preventive actions for the development of the SMEs sector.Intelligent data analysis, CRISP-DM, clustering, small and medium enterprises., Research and Development/Tech Change/Emerging Technologies, C8, L2,

Intelligent data analysis - support for development of SMEs sector

The paper studies possibilities of intelligent data analysis application for discovering knowledge hidden in small and medium-sized enterprises’ (SMEs) data, on the territory of the province of Vojvodina. The knowledge revealed by intelligent analysis, and not accessible by any other means, could be the valuable starting point for working out of proactive and preventive actions for the development of the SMEs sector

Utilization of intelligent methods and techniques for customer knowledge management

In order to achieve better market position, companies need to develop customer-centric strategy and properly manage customer data at their disposal in order to obtain useful knowledge. However, conversion of customer data into customer knowledge is very challenging. Data mining methods and techniques search for hidden relationships and patterns in corporate databases, and herein lies their advantage in the process of generating the knowledge. The paper illustrates application of data mining techniques for improvement of marketing activities

UTILIZATION OF INTELLIGENT METHODS AND TECHNIQUES FOR CUSTOMER KNOWLEDGE MANAGEMENT

In order to achieve better market position, companies need to develop customer-centric strategy and properly manage customer data at their disposal in order to obtain useful knowledge. However, conversion of customer data into customer knowledge is very challenging. Data mining methods and techniques search for hidden relationships and patterns in corporate databases, and herein lies their advantage in the process of generating the knowledge. The paper illustrates application of data mining techniques for improvement of marketing activities.Knowledge management, customer relationship management, data mining.