I've done some data modeling, and much more process modeling, so I was familiar with Mr. Hay's objectives with respect to data and restricting the model to logical representations of data, whatever that may be.
About six chapters into this book, I realize that while I could continue through to the end, I would likely find this more useful as a companion to a problem. I think the majority of non-academic readers, software practitioners if you will, will extract the necessary value from owning this book given a specific objective, i.e. I have to develop a work management model from scratch, and these are my (current) business rules.
The book covers so many kinds of models that it's entirely possible a reader will have no practical frame of reference, such as the chapter on accounting. Modern accounting software is primarily off-the-shelf, so developing a data model for it isn't something very common today. However, the smart developer understands that living "in the spaces between" software is a very good line of business, so to that end knowing what an ideal data model might have is certainly valuable ammunition when weighing vendor claims and evaluating solutions.
Because it lacks that sort of accessible readability, I am withholding a star. I'd have withheld a half-star if it were possible; I believe the book has great value to a developer or analyst.