Moving the Goalposts for Data Models … Deliberately
A practitioner recently said this: “Even if we assume that a technical methodology might exist to generate a complete and correct data model from a set of articulated business rules / facts, in my opinion this approach just moves the target from the data modeling area to the need to verify the articulation of business facts / rules for completeness and correctness.” Exactly! And why would that be a problem?! Here’s an additional advantage: The core concepts (concept model or fact model) of an operational business area are very, very stable. Don’t believe it? As proof see http://www.brcommunity.com/b594.php (short case study, well worth a quick read). The problem with current data modeling practices is that a large gap often exists between the business view of things (operational business things) and the ‘data’ view of those things – even when trying to keep to a ‘conceptual’ view. This gap gives business-side people a ready excuse to drop out. But data modelers alone can’t provide the necessary business know-how for a robust, complete model. The problem is so big, it’s hard to see. Current data model practices evolved bottom-up, from database designs. (I believe I can speak with some authority here. I was editor of the Data Base Newsletter, 1977-1999, and wrote three books related to the matter in the late ‘70s and early ‘80s.) It’s time for us to approach the problem top-down. There is a natural way to build concept systems – it starts with basic business communication. The standard for such an approach already exists – SBVR. (For discussion see BRCommunity’s SBVR Insider section.) We’re already living and working in a knowledge economy … We need to start acting like it!Tags: concept model, conceptual data model, data model, fact model, SBVR