{"title":"Common quality measures for Enterprise Architecture","authors":"Aarti M. Karande, Padmaja Joshi","doi":"10.1109/ICCSA57511.2022.00017","DOIUrl":null,"url":null,"abstract":"Enterprise architecture (EA) helps organizations in decision-making. Organizational performance space is used to measure the quality service values provided to all stakeholders. Developing common quality measures for business domain-based EA, is the need of the current Industry. Quality management in EA helps to develop processes for intelligence, security, controlling, monitoring and many more. This paper focuses on the quality measurement framework for EA. This paper highlights on Product, People and Process as the three important components to measure quality in EA. Proposed quality framework shows mapping of EA layers w.r.t product, people and process. Product is a physical product or a service as a outcome of EA, which can be quantitatively measurable component. People are stakeholders responsible for standard roles which can be qualitatively measurable. Process measures the performance of the workflow qualitatively. This mapping generates output either as a Information or as a Execution. Information can be measured quantitatively or qualitatively formulated based on reports, data analysis, analytical patterns or many more. Execution measures the outcome using quality parameters such as operation, performance, portability, maintainability and usability. EA Quality framework metrics are defined for controlling, assessing and evaluating common quality parameters. This framework standardize the structure of EA to achieve its current and future objectives effectively. This framework can be enhanced in future to measure overall impact of quality on the business domain mathematically.","PeriodicalId":218147,"journal":{"name":"2022 22nd International Conference on Computational Science and Its Applications (ICCSA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 22nd International Conference on Computational Science and Its Applications (ICCSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSA57511.2022.00017","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
Enterprise architecture (EA) helps organizations in decision-making. Organizational performance space is used to measure the quality service values provided to all stakeholders. Developing common quality measures for business domain-based EA, is the need of the current Industry. Quality management in EA helps to develop processes for intelligence, security, controlling, monitoring and many more. This paper focuses on the quality measurement framework for EA. This paper highlights on Product, People and Process as the three important components to measure quality in EA. Proposed quality framework shows mapping of EA layers w.r.t product, people and process. Product is a physical product or a service as a outcome of EA, which can be quantitatively measurable component. People are stakeholders responsible for standard roles which can be qualitatively measurable. Process measures the performance of the workflow qualitatively. This mapping generates output either as a Information or as a Execution. Information can be measured quantitatively or qualitatively formulated based on reports, data analysis, analytical patterns or many more. Execution measures the outcome using quality parameters such as operation, performance, portability, maintainability and usability. EA Quality framework metrics are defined for controlling, assessing and evaluating common quality parameters. This framework standardize the structure of EA to achieve its current and future objectives effectively. This framework can be enhanced in future to measure overall impact of quality on the business domain mathematically.