Is Data Modeling Still Relevant

From the FINETIK blog:

Some people believe data modeling has become very passé these days. The belief is that because data modeling theory is more than 30 years old and, because some data modeling tools have been around for 10 to 20 years, somehow data modeling is no longer relevant. Nothing could be further from the truth. In fact, data modeling may now be more necessary than ever before.

While there are other modeling techniques and notations, such as business process modeling and Unified Modeling Language, the need to accurately capture business data requirements and transform them into a reliable database structural design is as paramount as ever. The key differentiator is that data modeling is the only technique and notation that focuses on the “data at rest.” All the others tend to focus more on “data in motion.” Put another way data modeling concentrates on issues that lead to a solid database design, while others approaches tend to focus more on issues that will result in better application design or things useful to programmers, such as data structures, objects, classes, methods and application code generation.

Case in point: I’ve personally served as an expert witness in several court trials where plaintiffs sued defendants for serious financial remuneration when custom database applications had performance and/or data accuracy problems. In every case, there was a failure to data model the business requirements. Thus, the data effectiveness suffered. Moreover, ad hoc database design, or database design using more programmatic-oriented techniques and tools, often resulted in inefficient database design. No amount of coding could overcome the resulting bad database design. So, in every case, the plaintiff won.