The Case Against Denormalization

The article discusses the problem with denormalization in data modeling, which can lead to incorrect or approximate solutions to problems. The author argues that it is important to assess the cost of design compromises and require data modelers to document the differences between normalized and denormalized data models. [summary] [comments]

Source link