The Design And Application Of Data Warehouse For Securities Industry

After several decades of development of the securities industry itself, a large number of business data has been accumulated in different platforms, including centralized transaction data, financial data, and CRM data. The key problem is how to convert these data into a unified data platform. Thus, to enable us to analyze the business value, study the characteristics of potential customers and existing customers, provide scientific support for company's decision-maker, improve the comprehensive competitiveness of the company, have a better view of the company's future direction. The establishment of the data warehouse system for securities industry is undoubtedly the best solution for the above problems.This thesis described the basic theory of data warehouse as well as the design and development process of data warehouse for the securities industry, based on transaction data from Company A in year 2010. This thesis demonstrates, by applying business structure of loading and implementing the business data warehouse for the securities industry in a hierarchical manner, and using different dimension table that is designed by using advanced Informatica ETL design tool with different loading strategies, design and deployment of data warehouse platform can be efficiently realized. The result has provided scientific example and practical guideline for construction of business data warehouse for the securities industry.In addition, this thesis also analyzed historical transaction data by using OLAP technology of Company BO. By using OLAP tool, business people can observe and analyze customer's transaction activities from different perspective. Business people can also measure contribution of different customers at different stages as well as business contribution of different branch.Finally, this thesis uses k-means clustering algorithm to analyze customer's transaction data which is stored in data warehouse for the securities industry, to analyze the trading behavior and characteristics of different customers, to classify trading clients, to provide different service strategies for different customers. This will play an important role for company to make marketing strategy, to optimize customer relationship and to enhance the profitability of the company.