{"title":"Enhancing the involvement of decision makers in data mart design","authors":"Fahmi Bargui, H. Ben-Abdallah, J. Feki","doi":"10.1504/IJDATS.2019.10018909","DOIUrl":null,"url":null,"abstract":"The design phase of a data warehousing project remains difficult for both decision makers and requirements analysts. In this paper, we tackle this difficulty through two contributions. First, we propose a natural language based and goal-oriented template for requirements specification that includes all concepts of the decision-making process. The use of familiar concepts and natural language makes our template more accessible and helps decision makers in validating the specified requirements, which avoids producing data mart that does not meet their needs. Secondly, we propose a decision-making ontology that provides for a systematic decomposition of decision-making goals, which allows new requirements to emerge. This automatic requirements elicitation helps analysts to overcome their lack of domain knowledge, which avoids producing erroneous requirements.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"130 1","pages":"148-175"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Analysis Techniques and Strategies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJDATS.2019.10018909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 2
Abstract
The design phase of a data warehousing project remains difficult for both decision makers and requirements analysts. In this paper, we tackle this difficulty through two contributions. First, we propose a natural language based and goal-oriented template for requirements specification that includes all concepts of the decision-making process. The use of familiar concepts and natural language makes our template more accessible and helps decision makers in validating the specified requirements, which avoids producing data mart that does not meet their needs. Secondly, we propose a decision-making ontology that provides for a systematic decomposition of decision-making goals, which allows new requirements to emerge. This automatic requirements elicitation helps analysts to overcome their lack of domain knowledge, which avoids producing erroneous requirements.