基于OLAP的多维数据金融系统的研究与实现

发布时间：2018-04-22 01:29

本文选题：OLAP + 数据仓库　；参考：《杭州电子科技大学》2013年硕士论文

【摘要】：随着金融市场的竞争日益激烈，从大量的历史交易数据中提取出利于制定最佳投资策略的有价值的信息显得十分重要，传统的数据处理和分析技术已经不能满足企业对于数据处理和分析的需求。当前的金融信息系统已经不能满足资金管理人海量数据的处理以及多样化展示的需求，无论是数据的查询、统计或者报表，现有的处理方式都是按照指定的要求来完成，这种方式很难获得数据中潜藏的内在信息，无法为用户提供高效的查询分析处理以及高互动的丰富用户体验。本文以基于OLAP的多维数据金融系统的研究与实现为背景，介绍了数据仓库和联机分析处理技术在金融数据存储和处理方面的应用，以及应用在富因特网应用技术的客户端呈现。本文研究的系统采用B/S/S结构，分为数据服务层、中间服务层和数据展示层三层体系结构，分层结构降低了层与层之间的依赖，有利于保证系统的稳定性和扩充性，满足用户当前需求和支持未来信息技术的扩充需求。数据服务层的主要任务是从传统关系型数据库中抽取数据，清洗、转换并加载到数据仓库中，通过OLAP服务器进行查询和分析操作并构造多维数据集，中间服务层应用WCF服务技术实现数据服务层和数据展示层之间的数据通信，最终实现用户在数据展示层观察数据并对数据进行基于Web的多维分析操作。本文的主要内容包括：首先简要讨论了数据仓库的定义、特点、体系结构和ETL过程，并介绍了OLAP的相关概念、多维分析方法以及数据存储特点等方面；其次设计了系统的三层体系结构，，并根据金融业务数据的特性和系统实现需求，确定了数据仓库中数据存储的主题和数据模式结构；接着介绍了实现中间服务层的WCF技术的通信模型和核心要素，以及WCF服务层和业务逻辑层的具体实现；最后引入了RIA（Rich Internet Application，RIA）技术——Silverlight的结构和关键技术，以及数据服务层的开发模式MVVM（Model-View-ViewModel）的结构与实现，并在该模式框架下应用第三方控件xamPivotGrid实现基于Web的上卷、下钻、切片、切块和旋转等多维分析操作。系统使用SQL ServerAnalysisServices实施数据仓库，并提供数据访问和分析服务。通过本文的研究，将联机分析处理和数据仓库应用到金融数据的查询和分析处理中，并结合使用Silverlight技术，为用户构建一个快速响应查询和分析需求，提供在线的多维分析操作，并具有更强互动性和更丰富用户体验的金融系统。
[Abstract]:With the increasing competition in financial markets, it is very important to extract valuable information from a large number of historical trading data that is conducive to formulating the best investment strategy. Traditional data processing and analysis technology can not meet the needs of enterprises for data processing and analysis. The current financial information system has been unable to meet the needs of massive data processing and diversified display of fund managers. Whether it is data query, statistics or reports, the existing processing methods are all completed in accordance with the specified requirements. In this way, it is difficult to obtain the hidden information in the data, and can not provide users with efficient query analysis and rich user experience. Based on the research and implementation of multidimensional data finance system based on OLAP, this paper introduces the application of data warehouse and on-line analytical processing technology in financial data storage and processing, and the client presentation of rich Internet application technology. The system is divided into three layers: data service layer, intermediate service layer and data presentation layer. The hierarchical structure reduces the dependence between layers and is helpful to ensure the stability and expansibility of the system. To meet the current needs of users and support the future expansion of information technology requirements. The main task of the data service layer is to extract, clean, convert and load the data from the traditional relational database, query and analyze the data through the OLAP server and construct the cube. The intermediate service layer uses WCF service technology to realize the data communication between the data service layer and the data presentation layer, and finally realizes the user to observe the data in the data display layer and to carry on the multidimensional analysis operation based on the Web to the data. The main contents of this paper are as follows: firstly, the definition, characteristics, architecture and ETL process of data warehouse are briefly discussed, and the related concepts of OLAP, multidimensional analysis method and the characteristics of data storage are introduced. Secondly, the three-tier architecture of the system is designed, and according to the characteristics of the financial business data and the requirements of the system implementation, the data storage topic and the data pattern structure in the data warehouse are determined. Then it introduces the communication model and core elements of WCF technology, and the implementation of WCF service layer and business logic layer. Finally, it introduces the structure and key technology of RIA(Rich Internet Application tier (RIA). And the structure and implementation of the development model of data service layer (MVVMU Model-View-View-View-View-ViewModel), and the application of third-party control xamPivotGrid to realize multi-dimensional analysis operations based on Web, such as rolling, drilling, slicing, cutting and rotating, etc. The system uses SQL ServerAnalysisServices to implement data warehouse and provides data access and analysis services. Through the research of this paper, OLAP and DW are applied to the query and analysis of financial data, and Silverlight technology is used to build a quick response to query and analysis requirements for users to provide online multidimensional analysis operation. And with a more interactive and richer user experience of the financial system.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13;F830.91

【参考文献】