Is Data Modeling a waste of time?

by Polun L
The article, “Why does Data Modeling Take so Long”, by Jonathan G. Geiger, is an answer to the question asked by one of the attendees at a conference. The author explains that data modeling is used for designing data structures for businesses. Also, he mentions that when we begin building data modeling work, we should consider the four major steps  involved in developing the data model which are Requirements and business rules gathering, Source analysis, Logical model development, and Physical model development. These steps would guide data modelers to construct a better data structure as well as a more extensible model for future needs. The first step of requirements of business rules gathering is that we first need to understand the requirements of business questions and respond to questions for various business subjects. Once we understand the business rules, we should be able to use those information to create a desired level of data model. The second step of source analysis is that we use the collected data to analysis the possibilities of use and condition because we need to make sure the collected data fulfills the business needs. Finally, logical model development and physical model development basically use all the previous analyzed data in order to develop and form  a data model quickly. Therefore, data modelers spend a lot of time on building data modeling because business rules need to be understood, and collected data needs to be analyzed so that a data model is good enough for businesses.


After I read the article, I now understand why we need to spend a lot of time on building data modeling. Data modeling is like a platform for us to collect all required or useful data for building a good database. Any lack of data would cause an imperfect database. Furthermore, once a good data modeling is created, it is easy for us to track any errors that may occur in a database in the future.


G.Geiger, J. (2011). Why does data modeling take so long?. Retrieved from

5 thoughts on “Is Data Modeling a waste of time?”

  1. Hi, I enjoyed reading your article and agree with the overall concept. There are always short-cuts to be taken when writing software. In the long run, it is more efficient to take time to fully understand how it should be structured before designing a database. It could save a lot of time, money, and might even result in better performance.

  2. Polun, I updated the post image you used so it fits the screen better, and the thumbnail version on the blog site page also worked better accordingly. I did it by finding your original picture from the post image URL source, re-sizing the original picture in Photoshop and paste to a canvas of 663×274 pixels – the default by the blog site theme. I think my previous advise of using pictures 300×300 pixels only applies to the post content, if you are to use post image then it has to be 663×274 (or at least proportional relative to that so it will be stretched about evenly) to look in its best. I will let the class know next time.

  3. Great information regarding data modeling, thank you very much. I agree that data modeling is very important, however time consuming. We should also always consider ways to make work more efficient and find ways to save our valuable time. Finding a good median that fulfills all requirements with high performance yet allows us to save time would be perfect. Again, great info, thx!

  4. Every goal needs a plan and an organized plan needs a set of guidelines. This information is great because it talks about the certain importance of why business data modeling important. When I interned for a company as a web developer, the certain steps were the same because it’s always the same process. Collect data, turn it into information and then execute with great performance. Great article!

  5. Maybe someone who knows exactly what they want to code this may work. For the majority of us it beneficial to write out and plan and design, if not just for us but for clients as well (documentation is always important). The benefits outweigh the negatives of wasted time. You may waste more time if you don’t use data modeling.

Comments are closed.