Moving the Goalposts for Data Modeling … Deliberately. Hey Guys, We’re in a Knowledge Economy.Is there any proven way to demonstrate data models are correct, complete, and stable with respect to the operational business and its needs? No. That’s distressing. Is there an alternative that does? Yes, fact modeling, which is to say structured business vocabularies (concept systems). The core concepts (fact model) of an operational business area are very, very stable. I have outstanding proof (short case study). See: http://www.brcommunity.com/b594.php. Definitely worth a quick read. I recently made these statements in a data modeling forum, and a practitioner came back with 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, IMO 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.” Missed the point. Concept anaysis is brain work. You’ll never generate a ‘complete and correct data model’ … you must create it … ith business people and SMEs. The problem with data modeling as practiced today is that there is a large gap between the business view of things and the data model. It gives business-side people a ready excuse to drop out. And its an art rather than a science. You really have no justification building a system until you have a concept blueprint. Currrent data models evolved bottom up, from database design. (I know, I watched it happen. I was editor of the Data Base Newsletter, 1977-1999.) It’s time to approach the problem top-down. There are natural ways to build concept systems. The standard for the new approach is SBVR. (For more, see BRCommunity’s “SBVR Insider”), which in turn is based on ISO 1087 and 704. We (all of us) need to start practicing like we’re living in a knowledge economy … which in fact we actually already are.
Tags: data model, fact model, SBVR, structured business vocabulary