Why did you feel the need to say "you don't even care about the basics of data modeling"? I thought it was an interesting case, but now your reaction is the interesting item in this thread 😉
So tell me about why you believe I don't care or didn't care when I produced this system?
Let me start by appologizing for my harsh language - didn't mean to be offensive but I recognize it didn't come out that well.
Having said that, the process of data modeling is pretty straight forward - after getting your business requirements and collecting the data you need to work with what we usually do is:
1- Create a ER model where we identify the Entities that make up our system as well as the Relationships between such Entities.
2- After having a validated ER model we usually decide either to go with a Relational Physical Model or with a Dimensional Physical Model. First option which I prefer for OLTP systems requires to normalize data usually not below the 3NF; second option which I prefer for DSS a.k.a. Data Warehouse systems requires to develop a star-schema model.
In this particular - and certainly interesting case - I didnt' see a single trace of these expected steps therefore I assumed you decided to be adventurous and don't care about traditional data modeling techniques.
It also surprised me that the stated objective of the design was to favor data entry over reporting when each piece of data will enter the system just once but will be used for reporting forever after - this fact of life usually means that the underlying design favors "reporting" over "data entry" by creating a data structure that favors the process of retrieving the data.
Having said all of that, at the end of the day it don't matter if the cat is white or black, all that matters is the cat getting the mice.
Sorry again, no personal offense was meant.
Pablo (Paul) Berzukov
Author of Understanding Database Administration available at Amazon and other bookstores.
Disclaimer: Advice is provided to the best of my knowledge but no implicit or explicit warranties are provided. Since the advisor explicitly encourages testing any and all suggestions on a test non-production environment advisor should not held liable or responsible for any actions taken based on the given advice.