Research On Key Technologies Of Data Quality Management Of Data Warehouse For Commercial Bank

In recent years, with the development of domestic financial system reforms and Internet finance, the bank industry, especially commercial bank, is facing unprecedented competitive pressure. In order to expand the market, commercial banks have to investigate potential users deeply and promote operation precisely,while both of them depend on a data warehouse and data mining applications. A data warehouse provides foundation not only for centralized data management and application, but also for data analysis, data mining and other decision-support systems. Therefore, many commercial banks have deployed enterprise data warehouse systems.Nevertheless during the process of building a enterprise data warehouse, the huge amount of data and complex business logic will leads to a variety of problems affecting data quality. As it is well konwn for a data warehouse, data quality is particularly important which influences the quality of decision-support system and the results of analysis and mining directly. Therefore, how to ensure data quality is an important issue for a data warehouse project.The main work of this paper is focuses on the causes of data quality problems, explore the data quality assessment model and design data quality improvement methods. These methods includes data quality assessment model and calculation, data processing standards and data quality assurance methods in ETL processing. These methods are applied to the implementation of data warehouse projects.