A. Podaras, Tomas Zizka, D. Nejedlová, David Kubat
{"title":"A BUSINESS INTELLIGENCE SOLUTION FOR BUSINESS CONTINUITY AND SAFETY MANAGEMENT IN PUBLIC UNIVERSITIES","authors":"A. Podaras, Tomas Zizka, D. Nejedlová, David Kubat","doi":"10.33543/1002357365","DOIUrl":null,"url":null,"abstract":"The article introduces a modern business intelligence solution for facilitating business continuity and safety management proactive decisions in public organizations and units, which is currently tested in a public university for its effectiveness. The tool’s data dimensions, hierarchies and facts are based on the business continuity points method which is a modern approach for estimating proactively the recovery time and predicting the criticality level for individual business functions. From the constructed dataset, selected safety – related and highly critical business functions are used to validate the proposed contribution. The same functions are further used for estimating their availability rates and compare the results with the rates proposed by the university business continuity experts. The conducted research results indicated high accuracy when predicting criticality levels as well as computing availability rates for safety critical functions in the public university. The proposed BI tool facilitates both online analytical processing operations as well as machine learning activities.","PeriodicalId":409470,"journal":{"name":"AD ALTA: 10/02","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AD ALTA: 10/02","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33543/1002357365","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 article introduces a modern business intelligence solution for facilitating business continuity and safety management proactive decisions in public organizations and units, which is currently tested in a public university for its effectiveness. The tool’s data dimensions, hierarchies and facts are based on the business continuity points method which is a modern approach for estimating proactively the recovery time and predicting the criticality level for individual business functions. From the constructed dataset, selected safety – related and highly critical business functions are used to validate the proposed contribution. The same functions are further used for estimating their availability rates and compare the results with the rates proposed by the university business continuity experts. The conducted research results indicated high accuracy when predicting criticality levels as well as computing availability rates for safety critical functions in the public university. The proposed BI tool facilitates both online analytical processing operations as well as machine learning activities.