The Study On Data Warehouse And Data Mining In Telecom Industry Management Analysis And Application

The thesis applies Data warehousing and Data Mining to build an enterprise management analysis system (EMAS) which origins from ChongQing Unicom company. The aim of EMAS is to build a unionizing data information platform which takes advantage of the advanced Data warehouse and Data mining to extract the value information from enterprise management data to support effectively the enterprise management and market service, and promote the capacity of operation and competition, all these exhibit the customer orientation idea.On the technology theory, EMAS involves in database, On Line Analysis Processing(OLAP), Data Mining, artificial intelligence and statistics, etc; on the technology implementing, EMAS involves in a few kinds of system and tools integrated. So smooth connecting between technologies and the platform should be taken into account when EMAS is built.The thesis describes the general structure and network structure, expatiates on the keystone content to build an EMAS and presents the case of EMAS system analyzing.The thesis describes the whole procedure to build an EMAS from data source ETL to confirming theme range of data warehouse.On the data accessing, the core of OLAP and data mining is described, standing out the concept of "DOOR" in OLAP/real query/predefining report forms, and providing the OLAP analyzing process in the management analysis system through combining with management analysis theme.On the data mining, the thesis describes the mining method and mining process in common use. Combining with telecom business requirement, the applying data mining to telecom field is analyzed.The thesis also describes the detail content in the two management analyses. Each one provides the basic structure and data source of the FACT tables, and at the same time, lists the corresponding relation between data warehouse theme field and identifying entity.In the last chapter of technology specification, the case of OLAP and data miningis listed which illustrates the procedure of OLAP and DATA mining and analyzes the express forms of relative results.