The Research And Implementation Of The Key Technology Based On Banking Data Warehouse System

With the breakthroughs in information technology and rapid development, dissemination of information cost is significantly reduced, ease of access to information and greatly improve accessibility promote the rapid development of information society. In a knowledge-driven 21st century, more and more enterprises recognize the importance of information, information and data analysis has become the core of modern enterprise management. After years of financial electronic construction,banks has accumulated a large number of data reflecting the bank's management.However, due to lack of unity of planning and information standards, most of the bank's business data is not high quality, low reliability which hinder the bank's decision-making of managers. Use of data warehouse technology for the bank to build an analytic system to help banks improve manage decision-making level is the main purpose of this research project.Based on full understanding of the theory of data warehouse, a deep research on the architecture and key technologies of data warehouse is done on the background of a data warehouse project of a bank in this paper. To sum up, our works and achievements include as following:1.Improve the architecture of data warehouse on the basis of the study of the traditional advantages and disadvantages of data warehouse architecture. By taking ODS system identified by ClassⅠas a part of data warehouse, the three-tier architecture DB-ODS-DW can be formed, providing a quasi-real-time analyzing environment for data warehouse, and,to go a step further, satisfying users more perfectly.2.Considering such a fact that ODS system of ClassⅠneeds to extract the characteristics of data from the source system, the traditional acquisition strategies for changing data are analyzed and compared.And a real-time data extraction strategy based-on the database log analysis is proposed and implemented by Informatica extraction tool. 3.The implementation of the key technologies is introduced and discussed in detail during the implementation of the system combined with the detailed implementation stage, including the modeling the data warehouse, data storage strategy, data load slowly changing dimension strategy and etc.4. Test and optimize the system in the simulation environment to verify the feasibility of the system framework, ensuring the stability of the proposed system in a practical environment.