{"title":"Generating data mart schema from OLAP requirements","authors":"Nouha Arfaoui, J. Akaichi","doi":"10.1109/ICITES.2013.6624066","DOIUrl":null,"url":null,"abstract":"Warehousing projects can know cases of failure because they did not take into consideration the users' needs especially if they are not experienced with the technologies of data warehouses. The solution consists on building the data warehouse incrementally by designing and implementing one data mart at a time. In this work we propose a method to design data mart schema from OLAP requirements that are presented as schemas and grouped according to their domain. We apply the data integration technique to merge the different schemas so that we get one data mart schema by group. The integration is composed by schema matching (detecting semantic correspondence and the conflicts) and schema mapping (solving the existing conflict).","PeriodicalId":385126,"journal":{"name":"2013 3rd International Conference on Information Technology and e-Services (ICITeS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 3rd International Conference on Information Technology and e-Services (ICITeS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITES.2013.6624066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Warehousing projects can know cases of failure because they did not take into consideration the users' needs especially if they are not experienced with the technologies of data warehouses. The solution consists on building the data warehouse incrementally by designing and implementing one data mart at a time. In this work we propose a method to design data mart schema from OLAP requirements that are presented as schemas and grouped according to their domain. We apply the data integration technique to merge the different schemas so that we get one data mart schema by group. The integration is composed by schema matching (detecting semantic correspondence and the conflicts) and schema mapping (solving the existing conflict).