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dc.contributor.authorVacaflores, Thais
dc.date.accessioned2023-05-03T00:00:24Z
dc.date.available2023-05-03T00:00:24Z
dc.date.issued2022-12
dc.identifier.urihttp://hdl.handle.net/20.500.12648/8658
dc.description.abstractData modeling is the process of analyzing and defining the different data a business collects and produces and the relationships between that data. [8] Today there are two prevalent database models; relational modeling and dimensional modeling. These models are used to connect the various tables in a database to be used for data analysis. Most traditional businesses use a relational database to store all of their information, and when attempting to analyze data, the relational database is turned into a dimensional one. Dimensional models are considered to be simpler and better to execute queries against. Dimensional modeling is the current industry standard when analyzing data using a business intelligence tool, but are there cases when the transformation step can be skipped and a developer work with a relational model with minimal impacts on the development and user experience? This project will evaluate various aspects, such as the complexity of each model, query execution time, and time to update report elements on business intelligence tools as a result of user interaction. As well as determine if there are cases where the conversion step from a relational to a dimensional model can be skipped and queries created against the relational model instead.en_US
dc.language.isoen_USen_US
dc.subjectdata modelingen_US
dc.subjectrelationalen_US
dc.subjectdimensionalen_US
dc.titleA Comparison Between Relational and Dimensional Model Techniques in a Business Intelligence Settingen_US
dc.typeMasters Projecten_US
dc.description.versionNAen_US
refterms.dateFOA2023-05-03T00:00:25Z
dc.description.institutionSUNY Polytechnic Instituteen_US
dc.description.departmentDepartment of Computer & Information Scienceen_US
dc.description.degreelevelMSen_US
dc.description.advisorReale, Michael
dc.description.advisorJofre, Ana
dc.description.advisorSarner, Ronald
dc.description.advisorSpetka, Scott
dc.date.semesterFall 2022en_US


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