Apologies on being MIA and a quote from Abraham Lincoln

I started a new job (at CA, Inc.) and had to take a bit of time to learn the company and my role. Now that I am settled in (as much as one can ever settle in :-)), I can get back to devoting some time to blogging. With the disclaimer that ...

The opinions and statements on this site are my own and do not reflect the opinions or policies of CA, Inc.

So, onto my return post, I simply want to publish a quotation from Abraham Lincoln that is very relevant to semantics and models ...

How many legs does a dog have, if you call his tail a leg? The answer is four, because calling a tail a leg doesn't make it a leg.

It is unbelievable how often I hear things like "just change the name/representation of foo to be bar and we can get alignment". However, the real issue is not the representative name (which should indeed be clear), but the semantics that the people used, who defined the word "foo" in the first place. If we could move modeling to more than words on a UML diagram, to analyzing semantics ... we would be much better off.

Another thing that I sometimes hear is the question "what makes an instance a foo"? For example, "if I magically change the color and size of an elephant is it still an elephant?" Or, riffing on Nassim Nicholas Taleb's theory, "is a black swan a swan?" Semantics will help us understand what being a swan or an elephant or an IT service means - beyond the name. And, we have an added benefit ... if we make the essential definitions clear, then we have a better way to correct invalid definitions by removing problematic clauses (such as "all swans are white").

Andrea

Types of Models - For Business Versus For IT

I was looking through my notes about articles that I had read - and found an interesting Burton Group report entitled Generalized and Detailed Data Models: Seeking the Best of Both Worlds. (I think that it was published earlier this year.) I must admit to having been both confused and intrigued by the title. :-)

In the paper, "generalized" models are those used to define database/storage structures and to find the general themes and fundamental aspects of the data (and its values). In short, they are the data models defined by IT to effectively and efficiently use the technologies that are in place (like SQL databases). Maybe "reduced" is a better word than "generalized" ...

On the other hand, "detailed" models are those that are useful to business people. They define and describe the information requirements of the business, and its vocabularies, rules and processes. They hold the details from the business perspective. Again, maybe another word like "conceptual" is better (since even the "generalized" models hold "details") ...

What is valuable is not the titles used for these models but their semantics. :-) The key message is that a business needs both types of models and they need to stay in sync. This is really important. The conceptual/detailed models hold the real business requirements and language. They haven't been reduced to basic data values whose semantics are lost in the technology used to define and declare them.

IMHO, a business loses information and knowledge when it only retains and works from the IT models. There is much to be gleaned from the business input and much value in keeping the business people engaged in the work. This is almost impossible once you reduce the business requirements to technology-speak.

As the report says, "do not allow generalized models to compromise your understanding of the business."