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There are lots of people who call themselves Data Architects, and they have produced even more Data Architectures. Every data system, in fact, has a data architecture – whether by design, or by chance. Not all of these data systems, unfortunately, have good Data Architectures. The question is, how do you tell the difference between a good architecture, and a not so good one?

I have to admit that I’ve been putting off completing part two of this article (see part one here). It’s a simple question, but the answer seems to not be an easy one.

Last week I attended the World Wide Data Vault Consortium (WWDVC for short), more on that in some upcoming articles. While at the WWDVC, I had the privilege of mingling with some rather brilliant people, many of whom were data architects. So, I asked them some questions.

No, I’m not suggesting that you make your data available to everyone on the internet. I’m talking about freeing your data from its tight fitting applications.

Applications are important. They guide you and your staff in the efficient execution of the processes that keep your company moving. Along the way, they allow (or even require) a variety of data to be entered. Your applications help (or should help) ensure that your data is correct, and complete, and up to date.

A few years ago, back in my college days, I was sitting in a class on writing for communication (as opposed to writing fiction, I suppose). Anyway, the prof was telling us how technical people are so prone to using jargon, and how bad that was for communication. “Never use jargon”, she said, “unless you are speaking to someone from your own industry”.

She never mentioned buzzwords, but I expect her advice would have been the same.