|
Verbish Models: How to Coax Semantics into Your Data Models
by Ronald G. Ross
If it were as simple as data models vs. process models, our industry would have resolved all the ‘big’ problems many years ago. But it’s not that simple.
In particular, there is the problem of how your company can make better, more consistent, more agile operational decisions. Related to that challenge is how it can retain knowledge in a form that is traceable, manageable and redeployable so the loss of baby boomers and/or vital SMEs doesn’t bring the company to its knees. And of course, we could always do a much better job of developing requirements and communicating about know-how than we do today. All those things lead inexorably toward structured business vocabularies and business rules.
Most data modeling techniques have always been noun-ish – oriented ultimately to the things to be stored in databases and data warehouses. But there has always been a verb-ish counterpart, best typified by the fact models of Terry Halpin and Sjir Nijssen.
This presentation examines traditional problems in data modeling that are handled better using fact models. Hear about how you can enhance your data modeling skills to gear up for semantics, as well as become more versatile and effective in your day-to-day practice. Learn why your company needs your special talent a lot worse than it may think.
- Why you should care about verbs as well as nouns
- Exploiting verbal patterns
- Why ambiguity matters
- Data models that aren’t “data” models
- Stepping up to business communication and business rules.
- A pragmatic, proven, well-grounded approach to semantics
|
