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Banking Data Warehouse System Based on Key Technology Research and Implementation

Author: WuYing
Tutor: XuDongPing；LiYongHua
School: Wuhan University of Technology
Course: Computer Science and Technology
Keywords: Data Warehouse Operational data store Data Extraction Slowly changing dimensions Online Analytical
CLC: TP311.13
Type: Master's thesis
Year: 2010
Downloads: 140
Quote: 1
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Abstract


As information technology breakthroughs and the rapid development of information dissemination costs are significantly reduced, ease of access to information and accessibility greatly improved , and promote the rapid development of information society . In a knowledge economy as the leading economic form of the 21st century, more and more companies recognize the importance of information , information and data analysis have become the core of modern enterprise management . After years of financial electronic construction, reflecting the Bank has accumulated a large number of active data bank management , but due to the lack of unified planning and information standards , most of the bank's business data is not high quality , low reliability , which hindered the banks managers decision analysis . Use of data warehouse technology to build an analytical model for the bank application system to help banks improve management decision-making is the main purpose of this research . Based on the full understanding of the data warehouse based on the theory of a bank as a data warehouse project as background, the data warehouse architecture and key technologies for in-depth study , mainly to do the following work: 1 ) the study of the traditional data warehouse architectures based on the advantages and disadvantages of the data warehouse architecture , adapted by the class I class ODS system formed in part as a data warehouse DB-ODS-DW -tier architecture , the data warehouse has a quasi- real-time analysis of the environment, but also nice to meet user needs. 2 ) For Class I Class ODS system requires real-time extract the characteristics of the source system data , change the traditional analysis and comparison of data acquisition strategy is proposed based on the database log analysis of real-time data extraction strategy , combined with the extraction tool Informatica be achieved . 3 ) the implementation phase of the system implementation process of combining systems modeling techniques for data warehousing , data storage strategies , data loading slowly changing dimension strategy and other key technologies to achieve specific implementation process of a detailed presentation and discussion . 4 ) simulate the actual application environment for testing and tuning the system to verify the feasibility of the system architecture ensures that the system is in the actual application environment for stable operation.

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