{"title":"Managing and mapping data lineage for business intelligence and analytics applications in health care","authors":"Mana Azarm, F. Nargesian, L. Peyton","doi":"10.1109/I-SOCIETY18435.2011.5978521","DOIUrl":null,"url":null,"abstract":"The data delivery architectures in most enterprises are complex and under documented. When a Healthcare manager looks at a report, they want to know exactly what each element or technical expression on a report means, where the values shown originate from and how often they are getting updated. We propose a tool framework that includes: a meta-data repository for each step in the data delivery architecture; a web based interface to access and manage that repository; and mapping tools that capture data lineage to support step by step automation of data delivery. We illustrate and evaluate our approach with a prototype implementation and a case study using a health care analytics dashboard for managing hospital acquired infections.","PeriodicalId":158246,"journal":{"name":"International Conference on Information Society (i-Society 2011)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Information Society (i-Society 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SOCIETY18435.2011.5978521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The data delivery architectures in most enterprises are complex and under documented. When a Healthcare manager looks at a report, they want to know exactly what each element or technical expression on a report means, where the values shown originate from and how often they are getting updated. We propose a tool framework that includes: a meta-data repository for each step in the data delivery architecture; a web based interface to access and manage that repository; and mapping tools that capture data lineage to support step by step automation of data delivery. We illustrate and evaluate our approach with a prototype implementation and a case study using a health care analytics dashboard for managing hospital acquired infections.