Practice and application of distributed data quality management system in power enterprise - Yuanning LI; Sen LIU; Shijun ZHANG; Feng CHEN; Zhiying WANG (Dianxin kexue)
As the improvement of the enterprise’s informationalization level and the increasing management requirement of enterprise refinement，the demand of data management of enterprise is becoming greater and greater，how to improve the data quality of the enterprise is the key problem needed to be solved. Aiming at the challenges of data quality management that the power enterprise faces，some solutions for distributed data quality management were proposed. After researching the system features of data quality，some foreign and domestic cases of big data were analyzed as reference，and a solution based on Hadoop distributed processing framework was given to solve the performance bottleneck of centralized data quality system. Hadoop clustering could dissociate defect data from Oracle and the data would be stored separately on multiple servers of the clustering，which could improve the I/O performance and data analysis performance of the magnetic disk effectively.