NEW QUESTION 181
A Lead System Architect (LSA) team has a task to automate a design solution grading system.
Graders use the system to capture the score using a rubric (instructions) defined for the scenario. The rubric contain questions and statements against which the evaluation occurs.
The submitted design solution can fall into one of four categories: Excellent, Good, Not Bad, Bad.The score for each of these four categories varies between different versions of the instructions. For example, an Excellent score is anything above 75 in version 1.1. In version 1.2, a score above 65 is Excellent.Exam results are decided based on the average of the question scores.The result is either Pass, Fail, or Fix. For example, a total score between 60 and 75 is considered Fix.
The results range is version-dependent.Now, there is a debate within the team as to what data types the team should create.
Which one of the following options is the best data model design and implementation approach for this requirement?