資源描述:
《數據倉庫和數據挖掘技術在商業(yè)智能中的分析與應用》由會員上傳分享,免費在線閱讀,更多相關內容在學術論文-天天文庫。
1、江蘇科技大學工學碩士學位論文關鍵詞商業(yè)智能;數據倉庫;聯機分析處理;數據挖掘;直接營銷;交叉銷售IIAbstractAbstractAlongwiththedevelopmentofinformationtechnology,enterpriseinformationmanagementsystemhaspreservedalotofdata,includingproductionoperations,sales,customers,products,andotheraspects.Butthetradi
2、tionalinformationsystemswerelackingineffectiveanalyticalmethodsandtechnologies,thesehugedatawereburieddeepintheirsystemofequipmentwhichmadeenterprisesintheawkwardsituationof"datamore,informationless".SoBusinessIntelligence(BI)cameintobeinginthelate20thcen
3、tury.BImainlyusesthreecoretechnologieswhichareDataWarehouse,OnlineAnalyticalProcessingandDataMiningtoprocessandanalyzebusinessdataandassistuserstosolvetheuncertaintyencounteredinbusinessactivities,sothattohelpandperfectmanagementdecision-makingtoimproveth
4、eirviability.BIhasdevelopedrapidlyduring1990s.Inrecentyears,hotspotsofBIresearchmainlyfocusonsupportingtechnology,systemstructureandapplicationsystem.Thispapermainlystudiesonbothsupportingtechnologyandapplication.Thetraditionaltransactionprocessingdatabas
5、etechnologycannotmeetthecomplexbusinessinformationprocessandanalysisdemandofmodernenterprise,in1991,W.H.Inmonfirstputforwardtheconceptofdatawarehouse.ThispaperfirststudiesthebasicprincipleofdatawarehouseanditsrelationshipwithBI,andthencreatesadatawarehous
6、ewiththethemeofsalesandinventorybasedontheSQLServer2008BIplatform.TraditionalOn-LineTransactionProcessinghasfailedtomeetthemulti-dimensionalandcomplexqueriesofenterprisedecisionmakers.Thispaperconstructsasalesandinventorymultidimensionalcubebasedonsalesan
7、dinventorydatawarehouse,andachievesanenterprise-classmultidimensionalandmulti-levelOLAPtechnologyonthebasisofSQLServer2008BIplatform.Dataminingcanfindnewbusinessmodelsfromcommercialdatawhichcanprovideenterprisewithdecision-makingandpredictingsupports.Abou
8、tDirectmarketingbusinessproblem,forthechainretailingenterpriseaccordingtoitscharacteristicsofmorecustomers,morestoresandrandomlyscatteredcustomerpurchasingbehavior,thispaperpresentsEMclusteringnaivebayesclassificati