4 Chapter 1 INTRODUCTION either impossible to construct, or not worth it--or is it just that those who have said so do not know how to do it? Then there are packages. Many said that these would be the death of data modeling. Were they right? How did they design the packages? How do you judge whether an application's data model is fit for purpose? In many cases applications need to be configured; how does this affect whether information require- ments are being met, now, and in the future? Then along comes enterprise architecture. What does this mean for data modeling? What sorts of data models do you need in an enterprise architecture? What other elements do they relate to? How does this affect change management? Data modeling is a challenging task. It is often seen as a black art that some people seem to have a facility for. So how can you evaluate a data model that you are presented with? If you find some problems, how do you change the data model so that you remove the problem without introducing new ones? Why is it that if you look at the data models produced by differ- ent data modelers for the same requirements, it is unlikely that