The study of CDM-BSC-based data mining driven fishbone applied for data processing

Data Mining Driven Fishbone(DMDF), which is whole a new term, is an enhancement of abstractive conception of multidimensional-data flow of fishbone applied for data processing to optimize the process and structure of data management and data mining. CDM-BSC(CRISP-DM applied with Balance Scorecard), which is developed from combination of traditional Data Processing Methodology and BSC for performance measurement systems. End-to-end DMDF diagram includes complex dataflow and different processing component and improvements for numerous aspects in multiply level. Balance Scorecard applied to CRISP-DM is a new methodology of improving the performance of Information and Data Processing. CDM-BSC-based DMDF provides integrated platform and mixed methodology to support the whole life cycle of data processing with comprehensive methodology. Data preprocessing, data Classification, Association rule mining and Prediction are the foundation and linkage of the whole data processing life cycle. DMDF supports combination of different mining component from strategy level, tactical level to abstractive level, and then re-engineered data mining process into execution system to realize reasonable architecture. CDM-BSC-based DMDF is a new direction of the structure of large scale information and data processing.