Implementition & Designing Of Deposit & Remittance Business Analysis System

Data warehouse is an information system construction of the new technology, it can collect the data through statistical analysis into valuable information. Data warehouse is a decision support system and online analytical application of a uniform data structure data. Data warehouse is mainly to resolve access to information from the database and data problems. Can make a modern enterprise platform for broader access to information, to provide enterprises with the future of decision support information.Data Warehouse is a scientific and technological development to a particular stage of the inevitable outcome. The emergence of data warehouse is not to destroy the database. At present, most of the data warehouse or relational database management system to management. It can be said, databases, data warehouse complementary and inseparable. Database is transaction-oriented design, data warehouse is subject-oriented design. Database General store online transaction data, the data warehouse is generally stored in historical data. Database design is to avoid redundancy, the general rules in line with the paradigm design, data warehouse design is intended to introduce redundancy, use of anti-paradigm approach to the design. The database is designed to capture the data, the data warehouse is designed for the analysis of the data, and its two basic elements are dimension tables and fact tables.Data warehouse system is composed of a data warehouse, data warehouse management systems, data warehousing tools composed of three parts. Is a theme-specific, real-time data collection in support of corporate management decision-making process. Construction of data warehouse is an information processing of data as a whole, the data warehouse through data cleaning, data transformation, data integration, data loading process to construct. Diversification of sources of data warehouse is the data of an information repository, the data stored in the provisions of mode.From the massive amount of data mining, and chaotic, random data, digging out implicit in the work, the user desire to know, valuable information and knowledge. Data mining can be used in the original data is structured (for example, the database available data), but also can be a semi-structured (such as graphics, text is also possible that voice, etc.), and even on the network is also possible that irregular patterns of data. Excavated the knowledge can be used for information management, process control, query optimization, decision support, etc. can also be used for data self-maintenance. There are many, and like the concept of similar terminology, such as from a database knowledge discovery, data fusion, data analysis and decision support.Knowledge discovery is a simplified way to extract information from large amounts of data in a technique, but this information is potentially unknown, but also has potential applications; knowledge discovery can be seen as a valuable information on the search process, which do not have to assume that or ask questions, but still find those who are not expected concern information; This information indicated that the relationship between data elements and patterns, it also through a complete, comprehensive information discovery and data analysis to find valuable informationBusiness analysis system of business operation support system based on data from other systems, build a unified enterprise data warehouse. The use of advanced data mining technology to help companies understand the business decision-making status of business and found that the advantages and disadvantages of business operations, forecasting future trends to help market and customer segments, guiding marketing and customer service for targeted marketing and efficient Customer Relationship Management on the implementation of the decision-making and the results of objective and accurate assessment.Decision-making information for the modern enterprise's survival and play an important role in seeking to develop. Policy-makers generally want to be able to analyze large amounts of data already available to understand the business trends. With the increasingly fierce competition in the financial markets, the postal company has only continued to strengthen internal management, improve work efficiency, in order to survive in the competition and development, Harbin City Post Office Technology R & D "pools business analysis and management system" view of the current post Reserve the actual needs of business processes, combined with the construction of an electronic system, successful experience in branch offices, the postal savings business, traditional business management changed from the manual management of network computers, the postal savings business management personnel from tedious manual calculations freed, both saving valuable human resources, but also improve work efficiency and quality of work. Remittance Business Analysis Management System research and development and business management for my postal savings bureau to provide high-quality and efficient business processing capacity, not only a new form of society under the new postal financial business development needs, but also through real-time, accurate Postal Savings Business Development master data for the postal savings business in the direction of the development of a reliable basis, in order to further improve the quality of their work and expand the development of postal savings business to adapt to the current market environment lay a solid foundation. As a leadership decision-makers should be how the increasingly complex data environment to get valuable information? With the improvement of database technology and data processing technology development, data warehouse (Data Warehouse, DW) arise.This paper describes the analysis and management of the postal savings system, the basic concepts and realization method. Analysis pools the needs of business analysis system, described the overall operation analysis system structure and network structure. Business Analysis with a combination of themes presented in the statistical analysis of operational analysis system of specific mathematical implementation process, and from the data warehouse, knowledge discovery and OLAP discussed many aspects such as the construction of data warehouse system. In data mining context, describes the methods commonly used in mining and mining processes. Combination of savings and remittance business requirements, analysis of the data mining technology in the field of application pools. Pools has been put into use since the operating system to help the postal users from a large number of heterogeneous data to analyze business information to obtain timely and effective running smoothly and achieved a certain degree of economic and social benefits.