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Key Technologies Of Business Intelligence And Implementation

Posted on:2009-02-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y HuiFull Text:PDF
GTID:2208360245961343Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
As commercial competitions intensify,business intelligent systems are playing a more and more crucial role in the running of commercial affairs. Business intelligence has been developed on the technique basis such as Data Warehouse,Online Analyzing and Proeessing system and Data Mining technique,etc. Its essential demonstrates the effective info-mining from historical data in great amount and subsequently the tracking of knowledge from useful info, for wining initiative and more commercial opportunity in furious market,business intelligence is needed to guidance business behavior and to assist decision-making.This paper introduces the base of Business Intelligence's technology briefly at first, and then does the research of correlative key technology of Business Intelligence around how to improve the querying efficiency of BI system, reduce the possessive memory space and how to build the association rules mining model. Mostly including: 1,Research on materialized view's optimizing algorithm in the data warehouse. The materialized view is an important means of increasing the execution efficiency of a data warehouse, but the storage of the materialized view costs space.The cost estimation model which its measurement standard is the time cost of query composed of the materialized view which has to be scanned during the query or the space size of fact tables and the storage cost of the materialized view is built and the optimization algorithms of the materialized view based genetic algorithms is designed,in order to minimize the sum of the storage cost of the materialized view and the time cost of the query.2,Research on structure of multidimensional data storage. The logic organization mode of multidimensional data is one of the keys of OLAP implementation, this thesis summarizes the two organizing ways of multidimensional data-relational mode and array mode thoroughly, and places emphases on the researches of array mode, including the storage structure of multidimensional data, the construetion methods of multidimensional arrays, the compressing methods of sparse arrays, the principles of dividing arrays into chunks and the access methods of chunk arrays, and also this thesis realizes a storage instance of array mode based on the above theoretic analyses.3,Research on the association rules mining model which based on the Apriori algorithm. OLAP is a fast query and analyze technology of sharable multidimensional data. This paper analyses the characteristics of the Apriori algorithm and then proposes a design method of OLAP mining model accord to the algorithm.The design of the dimensions and measures in data cube fully consider the characteristics of the Apriori algorithm to make the data cube materialize more middle data the algorithm needed. Study shows that this method presents well on flexibility and efficiency.Using the application of business intelligent as the background and the key algorithm of business intelligent as the research aim this paper arrays some new technology methods, at the end of this thesis, the researches are summarized and the future work is presented.
Keywords/Search Tags:Business Intelligence, Data Warehouse, OLAP, Data Mining, Association Rules
PDF Full Text Request
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