{"title":"Towards an assessment model of end user satisfaction and data quality in Business Intelligence systems","authors":"Sara Bouchana, M. Idrissi","doi":"10.1109/SITA.2015.7358431","DOIUrl":null,"url":null,"abstract":"While substantial business investment in business intelligence systems (BIS) is continuing to accelerate, there is an urgent need of specific and rigorous methods to assess their performance and effectiveness. There are some scholars that have handled the measurement of Business Intelligence (BI) from a value perspective; others have chosen to assess the BI process, while some have tried to rather evaluate the performance of BI systems. However, there are practically no empirical research papers at hand concerning the measurement of BI systems seen from a product perspective. Therefore, we propose in this paper a product oriented evaluation of two major aspects of BIS: end user satisfaction with the intelligence produced by BIS and the quality of the data conveyed to end users. By exploiting the lessons learned from prior attempts to measure those two dimensions in information systems, we present a new evaluation model that is based on an understanding of the characteristics and the intelligence produced by BIS. We then propose a list of dimensions to be assessed in an examination of the relationship between end user's satisfaction and the quality of data conveyed to them. In this paper, multiple definitions of business intelligence in the literature are presented; besides, business intelligence systems measurement from different points of view is addressed. The purpose of this paper is to present an assessment model of end user satisfaction and data quality in BIS that participates towards the development of an evaluation approach of business intelligence systems seen from a product perspective.","PeriodicalId":174405,"journal":{"name":"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITA.2015.7358431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
While substantial business investment in business intelligence systems (BIS) is continuing to accelerate, there is an urgent need of specific and rigorous methods to assess their performance and effectiveness. There are some scholars that have handled the measurement of Business Intelligence (BI) from a value perspective; others have chosen to assess the BI process, while some have tried to rather evaluate the performance of BI systems. However, there are practically no empirical research papers at hand concerning the measurement of BI systems seen from a product perspective. Therefore, we propose in this paper a product oriented evaluation of two major aspects of BIS: end user satisfaction with the intelligence produced by BIS and the quality of the data conveyed to end users. By exploiting the lessons learned from prior attempts to measure those two dimensions in information systems, we present a new evaluation model that is based on an understanding of the characteristics and the intelligence produced by BIS. We then propose a list of dimensions to be assessed in an examination of the relationship between end user's satisfaction and the quality of data conveyed to them. In this paper, multiple definitions of business intelligence in the literature are presented; besides, business intelligence systems measurement from different points of view is addressed. The purpose of this paper is to present an assessment model of end user satisfaction and data quality in BIS that participates towards the development of an evaluation approach of business intelligence systems seen from a product perspective.