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Data Warehouse Technique Research and Implementation

Author: YuanLianHai
Tutor: TaoHongCai
School: Southwest Jiaotong University
Course: Computer Applications
Keywords: Data warehouse Subject-oriented Online transaction analysis Data Mining Database
CLC: TP311.13
Type: Master's thesis
Year: 2002
Downloads: 517
Quote: 8
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Abstract


This article is from the two aspects of technology development and business needs, the historical necessity of the data warehouse. Online transaction system and online analytical system, there are many differences between traditional OLTP applications considering the efficiency of transaction processing and data warehouse data with subject-oriented, integrated, including historical data, the data is not frequently updated data changes over time and so, data organization in order to improve the efficiency of data access. Therefore, the data warehouse to meet demand decision support system for frequently accessed data, decision support systems several solutions, the most practical technology. Traditional decision support system solutions with technology is difficult, not easy to implement and other defects, thus limiting the development of decision support systems. The emergence of the data warehouse for decision support systems bring to life. The purpose of the design of the data warehouse is to improve the ability of decision analysis. For this purpose, the data warehouse design needs to consider many factors, including physical storage, metadata, and a variety of technology and software development methodology to speed up data access efficiency. The historical changes of the data warehouse architecture, enterprise data warehouse project must be appropriate architecture and physical implementation. The data warehouse from the initial implementation of the local data marts to the completion of the last enterprise-wide data warehouse, need to go through a long development cycle. Data warehouse development methods and traditional online transaction system uses the system development life cycle approach is completely different. The system life-cycle approach is demand-driven, application project is to design, develop clear business needs, the data warehouse project is data-driven, must be used repeatedly, the spiral method development. The design of a common data model for data warehouse is the ER model. Data warehouse methodology for the implementation of the data warehouse project reference. Data warehouse development life cycle including project planning, requirements analysis, design, construction, deployment and implementation of projects, technical training and operation and maintenance of several parts. The data warehouse project is to close the technology, data warehouse design, development methods must be combined with practice in conjunction with engineering practice, continue to accumulate experience in the engineering process. Only by taking the right approach, the data warehouse project ultimately will not fail. As a practical project, the end of this article through the university data warehouse project analysis, design, and to illustrate the steps and design features of the development of the data warehouse. The emphasis is on project analysis, to understand the needs and the design of the data model. Relatively simple to implement, the key is to note in the understanding of data extraction, the importance of metadata and data partitioning and granularity divided.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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