The Application And Research Of Data Warehouse Technology In Communications Business Analysis

With the continuous development of enterprise informatization, people's demand on the information extraction becomes complicated, diversified, data warehouse technology arises at the historic moment. Enterprise managers hope that they can obtained the implicit information through data warehouse system, then, they can point out and make timely solution to market changes by reasonable judgment. The data warehouse is a concept, is a new type of data organization and access method, it collections of data that facing the theme, integrated, time-varying and non-volatile and supporting management decision-making. The data warehouse is a kind of database, it stores is all sorts of integrated level data.It obtained date from scattered, heterogeneous data sources by extracting, conversion, and applied to the data warehouse, then it can provide analysis environment for enterprise policymakers and also can make reasonable decision on the basis of the scientific and reasonable conditions by enterprise policymakers.OLAP (on-line Analytical Processing) on-line Analytical Processing, it effective use of information resources of the data warehouse, It can make analysis decision-making to the data on the data warehouse according to different grain size strategy.It realized by client/server system structure, request to customer response rapidly, and her core of multidimensional analysis can show multidimensional data to the user.This paper analysis the basic theory of data warehouse, and combines with the practies of jilin tietong engineering to construt of jilin tietong communications business analysis data warehouse. This can provide reliable analysis environment for Tietong operators to better understand their own condition and market changes. In design of operation system of jilin tietong communications business analysis data warehouse, I analysis its business dimensions and theme based on the current situation of tietong operation system. and construct the star model of the data warehouse. In addition, I used the improving algorithm of outline connection on star model to improve the quering efficiency. Then according to its data condition, I analysis grain size and design of the partition, and completed the data warehouse to meet tietong on-line analysis demand. In design of scheme, I combined the data driven and demand driven. Then I carried on the detailed analysis and design to the data model of data warehouse, storage and data extraction, conversion and loading. Finally, through on-line analytical processing knowledge, establishing multidimensional data model, and display the reports structure before the user.