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Since the 1990s , with the proposed concept of data warehouse technology matures , domestic and foreign financial institutions began to apply data warehouse technology business analysis , profitability analysis, customer analysis , and achieved good profits and returns . Especially in customer analytics , customer relationship management ( Customer Relationship Management ) system established through the implementation of customer-centric business philosophy and the use of data warehouse technology , domestic and foreign financial institutions, especially investment banks, commercial banks and securities firms and so on, more competitive environment will have an advantage . Firstly, in-depth analysis of the current situation and data warehouse technology of domestic securities companies face fierce competition in the domestic and international financial institutions, the implementation of dynamic , discussed the current situation, development situation and prospects of data warehouse technology . Based on full understanding of the relevant industry knowledge of the securities industry , the analysis of a securities company's business status quo and development goals , the paper design a data warehouse for the company CRM system . For the company handling the large amount of data , the system uses a distributed data warehouse system and the three-tier architecture . Secondly, the paper focuses on the company CRM system for customer analysis for this purpose , the establishment of a data warehouse data model . Data model designed to confirm the four themes of the data warehouse system : customers, accounts, transactions , securities and its data granularity around the customer subject line ; due to the data warehouse for the company's CRM system to provide data , in-depth analysis , design the corresponding fact tables , dimension tables , indexing strategy , storage structures and storage strategies . Finally, the key technologies of the data warehouse system build process ETL ( Extraction - Transformation - Loading ) made ??a focus of research . Large amount of data and the problem of heterogeneous data , the data warehouse system data extraction , data interface, the data mapping and data cleansing loaded against the company source database system solutions , and the data warehouse system ETL discussion devoted to research .
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