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A Value Model-Based Decision Framework for an Enterprise Data Architecture

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dc.contributor.advisor Costa, Paulo C. G.
dc.contributor.author Fitzpatrick, Kelly
dc.creator Fitzpatrick, Kelly
dc.date 2021-12-03
dc.date.accessioned 2022-06-13T23:10:39Z
dc.date.available 2022-06-13T23:10:39Z
dc.identifier.uri http://hdl.handle.net/1920/12906
dc.description.abstract The objective of this paper is to improve an organization's decision-making process for developing an enterprise data architecture. Enterprise data architectures are complex systems with multiple users who have com- peting objectives for the system. When developing an enterprise data architecture, it can be hard to satisfy all the organizations goals and maintain a consistent development plan. The development team building the enterprise data architecture needs a robust decision- making process to help them determine the architecture design for the organization. The process needs to be able to quickly support questions that arise throughout the development of the system. The goal is to reduce the amount of time answering questions after a decision has been made on the architecture design and development plan. The solution presented is a framework that uses value focused decision analysis and model-based systems engineering to develop a parametric model which can be used to identify the best architecture design for the organization and support answering questions the organization's leadership might ask [1]. en_US
dc.language.iso en en_US
dc.subject enterprise data architecture en_US
dc.subject big data architecture en_US
dc.subject model-based systems engineering en_US
dc.subject multi-objective decision analysis en_US
dc.subject decision analysis en_US
dc.subject value focused decision making en_US
dc.title A Value Model-Based Decision Framework for an Enterprise Data Architecture en_US
dc.type Thesis en_US
thesis.degree.name Master of Science in Systems Engineering en_US
thesis.degree.level Master's en_US
thesis.degree.discipline Systems Engineering en_US
thesis.degree.grantor George Mason University en_US


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