Proposal and Evaluation of a Database Data Model Decision Method
Abstract: A common problem when choosing a data model for a database is that there are many aspects to take into consideration–making the decision difficult and time-consuming. Therefore this work aims to create a decision method that enhances the decision by making it more suitable for the use-case at hand as well as making it quicker. First, the Analytical Hierarchy Process, a multi-criteria decision method, was identified as a suitable framework that the created decision method was based on. It was developed iteratively and later validated through a survey at Omegapoint. The survey had 27 respondents, but 14 answers were discarded due to being too unreliable, which led to a total of 13 utilized responses. The decision method was implemented in a web application to simplify the survey process, where the respondents use the web application, and answered some follow up questions about the web application’s result and process. It was found that it is possible to create a decision method which makes the choice of a data model quicker and better suited for the use-case. The method is reliable among a subsample of the respondents in the survey as 11 out of 13 respondents found the decision method’s result to be reasonable. However, the small sample size makes it impossible to draw any statistical conclusions of the reliability of the decision method. Additionally, the decision method helps to make the decision quicker, but this is only proven among the respondents in the survey. Based on the results, we conclude that it is possible to create a decision method which makes the decision quicker and better suited for the use-case. However this is only proved among the survey respondents, and a future work could aim to repeat the validation in order to statistically validate the reliability of the decision method.
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