| With the development of science technology and concentration of the application systems and data in bank, the requirements of data analysis become more and more urgent. However, there are different standards, measures, data sources and results in the systems of bank. In order to support decision of operation and management, scientific management and lead business change, it is important to construct overall, uniform and shared data platform.The purpose of this thesis is to resolve the questions why building, how building, and how using the data platform so that it can be provided with direction and guide of building data platform of bank. I will studied them as follows:Firstly, the business aim and definition of the data platform are set up in order to unify the understanding through analyzing the problem which analysis systems confront in bank. The construction and implementation strategy are also made clear through comparing advantages and disadvantages of technical framework of DW, ODS, DM and so on while analyzing the requirement and situation of our bank systems. Meanwhile we put forward a whole architecture of fundamental data platform, via analyzing application, implementation strategy, technical architecture of data platform of many business banks.Secondly, after the aim?strategy and architecture of our data platform are determined, we need resolve several key technologies of data platform. This article researches the design and implementation of several key technologies of data platform including ETL, Data Module, Meta Data, BI Presentation, Big Data and Parallel Processing.Finally, It studies several applying scenes and patterns of data mining algorithm such as Clustering,Classification, Association Rules Mining, Outlier Detection in Bank. Compared with traditional application of data analysis and data mining, the solutions, such as crediting via internet, are discovered from internet?big data and bank business together. |
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