{"title":"监测企业信息系统使用情况的数据网站","authors":"D. K. Khalaf, Murtadha M. Hamad","doi":"10.1109/DeSE.2019.00059","DOIUrl":null,"url":null,"abstract":"Enterprise information system represents the most popular base in data generation and aggregation. Decision making depends on data generated by institutions. Webhouse can monitor the movement of stored data. Access to the optimal decision-based webhouse is remotely handled via the Internet. Healthcare enterprises are among the most important institutions that handle data for making informed decisions. This study presents the most optimal and simplest approaches for handling and controlling data from institutions. This study proposes an algorithm for entering, cleaning and purifying data for webhouse (called Web extraction–transformation–loading). It suggests an algorithm (called Web fragmentation) to easily and simply display data across the Web and build a receipt. Moreover, this study proposes an algorithm (called Web OLAP) for analysing stored data to arrive at a correct decision by constructing a query on the basis of the options determined by an organisation. The individual outputs of the proposed algorithms provide services to the beneficiary. The recommended system is used to call the last analysis of the queried data and the resulting decisions. The methods used in this study yield excellent results in terms of data recall and performance. The performance of the user leads to good results in appropriate decision making.","PeriodicalId":6632,"journal":{"name":"2019 12th International Conference on Developments in eSystems Engineering (DeSE)","volume":"50 1","pages":"278-283"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data Webhouse for Monitoring the Use of Enterprise Information System\",\"authors\":\"D. K. Khalaf, Murtadha M. Hamad\",\"doi\":\"10.1109/DeSE.2019.00059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Enterprise information system represents the most popular base in data generation and aggregation. Decision making depends on data generated by institutions. Webhouse can monitor the movement of stored data. Access to the optimal decision-based webhouse is remotely handled via the Internet. Healthcare enterprises are among the most important institutions that handle data for making informed decisions. This study presents the most optimal and simplest approaches for handling and controlling data from institutions. This study proposes an algorithm for entering, cleaning and purifying data for webhouse (called Web extraction–transformation–loading). It suggests an algorithm (called Web fragmentation) to easily and simply display data across the Web and build a receipt. Moreover, this study proposes an algorithm (called Web OLAP) for analysing stored data to arrive at a correct decision by constructing a query on the basis of the options determined by an organisation. The individual outputs of the proposed algorithms provide services to the beneficiary. The recommended system is used to call the last analysis of the queried data and the resulting decisions. The methods used in this study yield excellent results in terms of data recall and performance. The performance of the user leads to good results in appropriate decision making.\",\"PeriodicalId\":6632,\"journal\":{\"name\":\"2019 12th International Conference on Developments in eSystems Engineering (DeSE)\",\"volume\":\"50 1\",\"pages\":\"278-283\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th International Conference on Developments in eSystems Engineering (DeSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DeSE.2019.00059\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Conference on Developments in eSystems Engineering (DeSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DeSE.2019.00059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Webhouse for Monitoring the Use of Enterprise Information System
Enterprise information system represents the most popular base in data generation and aggregation. Decision making depends on data generated by institutions. Webhouse can monitor the movement of stored data. Access to the optimal decision-based webhouse is remotely handled via the Internet. Healthcare enterprises are among the most important institutions that handle data for making informed decisions. This study presents the most optimal and simplest approaches for handling and controlling data from institutions. This study proposes an algorithm for entering, cleaning and purifying data for webhouse (called Web extraction–transformation–loading). It suggests an algorithm (called Web fragmentation) to easily and simply display data across the Web and build a receipt. Moreover, this study proposes an algorithm (called Web OLAP) for analysing stored data to arrive at a correct decision by constructing a query on the basis of the options determined by an organisation. The individual outputs of the proposed algorithms provide services to the beneficiary. The recommended system is used to call the last analysis of the queried data and the resulting decisions. The methods used in this study yield excellent results in terms of data recall and performance. The performance of the user leads to good results in appropriate decision making.