We all know what a good data model is and spend significant time designing a good data model. So if there are good data models then there are bad data models too.
There is a difference between incorrect data models and bad data models. An incorrect data model would not satisfy business requirements and hence they don't make to the implementation. But bad data models would get implemented. They do more harm to the system. Every part of the application has to compensate for the bad data model.
Bad data models evolve due to various reasons – time and resource constraints, inexperience, over engineered modeling and sometimes sloppiness.
Subscribe to:
Post Comments (Atom)
1 comment:
Agreed and would like to add that a bad data model should also be looked as an indicator to larger problems in overall design/implementation of the project.
Post a Comment