The Application Of BUC Algorithm In The Bank Off-Field Auditing System

Modern information management and transport techniques invite the rapid development of off-field auditing in banks. Bank off-field auditing system is an analyzing-oriented system, which needs to realize the storage, query, analysis, management of massive and historical business data in banks.In a large sense, The Monitoring function of off-field auditing system realizes the risk evaluation by analysis of indicators, so the computing of indicators is an important background calculating engine. Considering the two characteristics of sparse data, organizing data based on RDBMS, we introduce the BUC Algorithm in this system which is used as the algorithm of CUBE-computation to calculate the numerous indicators quickly and effectively.This dissertation focuses on the realization and application of BUC Algorithm in bank off-field auditing system, and gains several meaningful accomplishments in the following aspects:With researching the experience of applying BUC Algorithm in similar systems, this dissertation firstly confirms the feasibility of BUC Algorithm in bank off-field auditing system.Then the following task is researching on BUC algorithm which is best suitable for calculating the sparse data and proposes a reformative algorithm, BUCPC to calculate PCUBE (Partial CUBE); at the same time, another job is researching on BUCPC-optimizing techniques.Finally, the dissertation works on applying the improved algorithm into a bank off-field auditing system. We design corresponding Data Model, metadata files and develop calculating program, which promotes the application of BUCPC in the modules of indicator and statistic computing.