An Efficient and Effective data clustering Technique for business and industrial applications in large databases

An Efficient and Effective data clustering Technique for business and industrial applications in large databases

Recent advances information technology has rapidly increased the amount of data stored in databases. For mining data in large organizational databases, efficiency, accuracy and ease of utilization are imperative. Hence, approaches of retrieving helpful information from large databases rapidly and effectively requires being explored in depth. Data mining allows a user to locate helpful information from an original data with a plurality of data sets, so as to discover implicit characteristics and relations among the plurality of data sets. Based on the characteristics and relations, a completed data analysis model can be constructed. The data analysis model can be employed in various fields such as spatial data analysis, document managements, business behavior analysis, internet invasion analysis and so forth. Accordingly, potentially critical information can be located for decision makers to reference. Data mining involves data clustering approaches that allow a user to fast detect intrinsic correlations among the plurality of data, such as consumers' purchasing behavior and age-based market segmentation.