Advancement in Data Modeling

by Joey L
This article focuses on why technical architects and data modelers should adapt and evolve their current modeling practices to an agile data-modeling scheme.  Modelers most likely would believe that when building a data model, they should design and implement every single aspect of the model before building software that uses its resources from the data.  In agile data modeling, however, vastly changes how data models are implemented.  Agile modeling takes on an increment development activities on modeling.  Models are first simply designed efficient enough to allow incremental development in the future.  Only the basic framework of the design is developed to support the current development of the project.  Details of the model that are not immediately needed is often omitted by an agile modeler.  By following this scheme for modeling development, only the intended purpose of the model is produced.

This article relates closely to this week’s topic: data modeling.  I find this article to be quite interesting.  It lists how adapting to an agile data modeling scheme will benefit the business in many ways.  Data models will “evolve toward excellence” by following a new set of practices which will allow a safe evolution of models.

I find this method of developing a data model to be very efficient.  Since this data model scheme only takes on the minimal requirements for a project, the data model could be finished at a faster rate.  Also since the basic model will much smaller than traditional model, there will be fewer defects in the system, easier to understand, and cost less to maintain.  There will be less unnecessary rework and unintended side effects from the modeling.  This method also incorporates a vast amount of flexibility.  Developers can refactor and alternate the model to fit the current circumstances of models that are already in production.   Overall, I think that modelers that adapt this kind of modeling practice will help innovate data modeling into becoming a much simpler task for modelers to handle.

Collier,K. (2011, June 22). Agile Data Modeling: Evolving Toward Excellence. Retrieved from


1 thought on “Advancement in Data Modeling”

  1. I think this type of modeling is really efficient and cost-effective. Make the structure (foundation) as simple as possible, but make it strong. Once the “mainframe” is built and functions well, new features can be added as seen fit. This way the most important functions don’t get mixed in with a bunch of unnecessary additions.

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