Boastful parent: “My son has been taking violin lessons for 17 years!”

Unimpressed listener: “You mean he still can’t play?”

Say what you will: I’ve been studying data modeling for thirty years. It is hard. Mastery eludes many because mastery requires not merely practice (artificial) and experience (real), but the combination of practice, experience, and concentrating as much on technique as on outcome.

An excellent outcome is undeniably a cause for rejoicing. But excellent technique, in all its persnickety glory, is a foundation for a lifetime of excellent outcomes. Data-modeling technique will be a recurring theme of this blog.

Another theme: Why is data modeling hard, and what if anything can be done to make it easier? To be sure, it is hard for legitimate reasons. There are some inescapable truths about culture, language, categorization, and technology that ensure that a modeling career will offer challenges and attendant gratifications. For example:

• Truth: Modeling with users should transpire in the users’ natural language, which is fraught with ambiguity. By contrast, the resulting model will ultimately yield — perhaps through automatic forward engineering — a rigorous specification of one or more components of a software system. Modeling is hard because it demands a reconciliation between the incoming ambiguity and the desired rigor.

Alongside the many legitimate reasons why modeling is difficult are some silly ones. What are these, and what can be done about them? Here things could get interesting, because many of these silly reasons have been institutionalized as modeling best practice. Stay tuned and expect some debunking, once a fortnight.

-Joe Maguire, co-author, Mastering Data Modeling: A User-Driven Approach

Some Disclosure:  Blog posts here will be written by me or my colleague Peter O’Kelly, another three-decade veteran of the industry. Although Embarcadero will compensate us for these posts, we are solely responsible for their content. (Proof: We are unconstrained. The best practices offered here might or might not align with what you’ll find elsewhere on the ER/Studio site, in ER/Studio documentation, or in Embarcadero-sponsored whitepapers.)