{"title":"UML-Based Data Warehouse Design Using Temporal Dimensional Modelling","authors":"G. Reddy, Suneetha Chittineni","doi":"10.4018/ijsppc.2020070101","DOIUrl":null,"url":null,"abstract":"The design of a data warehouse system deals with tasks such as data source administration, ETL processing, multidimensional modelling, data mart specification, and end-user tool development. In the last decade, numerous techniques have been presented to cover all the aspects of DW. However, none of these techniques stated the recent necessities of DW like visualization, temporal dimensions, record keeping, and so on. To overcome these issues, this paper proposes a UML based DW with temporal dimensions. This framework designs time-dependent DW that allows end-users to store history of variations for long term. Besides, it authorizes to visualize the business goals of organizations in the form of attribute tree via UML, which is designed after receiving user necessities and later reconciling with temporal variables. The implementation of proposed technique is detailed with university education database for quality improvement. The proposed technique is found to be useful in terms of temporal dimension, long-term record keeping, and easy to make decision goals through attribute trees.","PeriodicalId":344690,"journal":{"name":"Int. J. Secur. Priv. Pervasive Comput.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Secur. Priv. Pervasive Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijsppc.2020070101","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
The design of a data warehouse system deals with tasks such as data source administration, ETL processing, multidimensional modelling, data mart specification, and end-user tool development. In the last decade, numerous techniques have been presented to cover all the aspects of DW. However, none of these techniques stated the recent necessities of DW like visualization, temporal dimensions, record keeping, and so on. To overcome these issues, this paper proposes a UML based DW with temporal dimensions. This framework designs time-dependent DW that allows end-users to store history of variations for long term. Besides, it authorizes to visualize the business goals of organizations in the form of attribute tree via UML, which is designed after receiving user necessities and later reconciling with temporal variables. The implementation of proposed technique is detailed with university education database for quality improvement. The proposed technique is found to be useful in terms of temporal dimension, long-term record keeping, and easy to make decision goals through attribute trees.