A Comparison Between Relational and Dimensional Model Techniques in a Business Intelligence Setting

Abstract

Data 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.