Data can be categoriesed in a surprising number of ways, but in the end only one category really matters...

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 was asked the other day to explain how I would implement an architecture for meta data management as opposed to data management. The question actually stopped me for a moment because it is not a straight forward as it first sounds. In fact, it may be simpler than it sounds.

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.

Instead of talking about data today, I’m going to talk a bit about process. In particular, taking advantage of several services that have popped up recently that can help you to automate some of your processes.

Have you ever wanted to have a way to automatically thank everyone who follows you on Twitter? These services can do that. How about turning on your lights when you arrive home? Yep, you can do that too. Track the hours you spend at a the office? Easy. Make sure your profile picture is always the same on all your social media channels? Can do.

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.

A couple weeks ago, I was in a meeting and someone said something that really resonated with me, “Our data has grown somewhat organically”.

I love that statement, because it’s true of every organization regardless of size. Data really is organic. Not in the chemical sense, nor the the marketing sense (as in the "organic" section of your local grocery store), but in how it behaves. Data usually starts small, but it grows. It doesn't just grow in volume, but in scope, and in different directions. Data is like a tree in your yard. If it is taken care of, it will be healthy and strong. But it can also grow in ways that are not useful, like a hedge taking over a sidewalk, or a large branch of your favourite tree that threatens your house whenever the wind blows.