In the real world, good decision modeling is always a balance between science and art. The science is systematic decomposition of a structure (of data or logic) into a set of smaller structures based on the definitions of successive normal forms. The art, on the other hand, is a general decomposition into a set of smaller structures based on factors not related to detecting and correcting normalization errors.
How often has a customer asked you to write software that is user-friendly, robust, fast, or secure? No one will argue that those are worthy goals that everyone wants in their software products. However, they are terrible requirements. They give you no idea of just what “user-friendly” means, or how to tell if you’ve achieved the desired characteristics that mean “user-friendly” to a particular customer.
I’ve come to the conclusion that most projects produce better results when they have specialized people playing the various roles, rather than trying to be resourceful and wear multiple hats.
Visual models don’t have to be complicated. Unless your organization uses formal UML or BPMN standards, focus on learning to create simple visual models. In this article, we’ll explore 3 simple visual models that a new business analyst should be skilled in creating because they add a lot of value to projects and generally improve your requirements documentation.
Driving Lessons. We all did it. We all know how that very first one went. It was described to us that the clutch should be engaged, place the car in first gear, release the handbrake, release the clutch and press down on the accelerator… Only for the car lurch forward then stutter and lurch forward again. This process continues several times before the car stalls and comes to a stop.
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