M. Gebhardt, M. Jarke, M. Jeusfeld, C. Quix, Stefan Sklorz
{"title":"用于数据仓库质量的工具","authors":"M. Gebhardt, M. Jarke, M. Jeusfeld, C. Quix, Stefan Sklorz","doi":"10.1109/SSDM.1998.688130","DOIUrl":null,"url":null,"abstract":"We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.","PeriodicalId":120937,"journal":{"name":"Proceedings. Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Tools for data warehouse quality\",\"authors\":\"M. Gebhardt, M. Jarke, M. Jeusfeld, C. Quix, Stefan Sklorz\",\"doi\":\"10.1109/SSDM.1998.688130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.\",\"PeriodicalId\":120937,\"journal\":{\"name\":\"Proceedings. Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSDM.1998.688130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Tenth International Conference on Scientific and Statistical Database Management (Cat. No.98TB100243)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSDM.1998.688130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We show three interrelated tools intended to improve different aspects of the quality of data warehouse solutions. Firstly, the deductive object manager ConceptBase is intended to enrich the semantics of data warehouse solutions by including an explicit enterprise-centered concept of quality. The positive impact of precise multidimensional data models on the client interface is demonstrated by CoDecide, an Internet-based toolkit for the flexible visualization of multiple, interrelated data cubes. Finally, MIDAS is a hybrid data mining system which analyses multi-dimensional data to further enrich the semantics of the meta database, using a combination of neural network techniques, fuzzy logic and machine learning.