- Data Modeling's Promise?and Failure
- About Modeling Conventions
- These Models and Your Organization
- Who Should Read this Book?
Who Should Read this Book?
This book is intended to help the person who has learned the mechanics of data modeling and is now trying to learn the art. “O.K.,” a student says, “I understand how to read diagrams, but how do I go into my company and make sense out of the morass that I find there?” This book gives you a method for doing that. Instead of having to create models from scratch, you can pull a model or two out of this “tool kit,” and modify it to make it look like your company or agency.
This book can also help analysts who have been commissioned to analyze a particular application area, but who haven’t the benefit of a prior strategy study to put that area in context. In the absence of a strategy study, these models can provide a context within which to place models specific to your application. For example, you may be working in sales and know that, although there is an interaction with manufacturing, no one is looking at the plant to determine what that interaction will be. In this case, you can look at the manufacturing models described in this book, and at least see the dimensions and elements of manufacturing to consider.
Had a strategy study been done, you may assume that its general shape would be similar to the models presented here. The models in this book are based on models from many strategy studies in many industries.
Most of the business situations described in this book will be familiar to most readers, but some of the more specialized chapters cover territory unfamiliar to many. Modelers who use this book to broaden their understanding of how different aspects of business work will gain an additional benefit.
The remaining chapters in the book develop models of an organization, piece by piece. Each chapter describes a specific business situation, and presents a candidate data model, depicting the core elements of that business situation. In the course of the descriptions, possible variations are pointed out, along with the organizational issues that might call for one variation or another. The models generally build chapter by chapter throughout the book. Specific circumstances may require names to be changed as we go along, as the entity names encompass progressively more general concepts. This means that while in early chapters entity names are reasonably concrete, they will become progressively more abstract as we go along.
Again, the premise here is that each data model presented is a reasonable starting point for describing a typical situation. Think of this book as a model-building kit.
Chapter Two describes the three levels of conventions in more detail, setting the stage for what follows. In that chapter are presented the syntactic and positional conventions used in the book, followed by a more extensive discussion of what exactly is meant by semantic conventions.
The next five chapters treat general topics that apply to most companies and agencies. People and organizations are modeled in Chapter Three, the things the enterprise deals with are examined in Chapter Four, its activities and procedures are the subject of Chapter Five, its dealings with the outside world are covered in Chapter Six, and accounting is dealt with in Chapter Seven.
Chapters Eight, Nine, and Ten address more specialized topics. Chapter Eight describes a laboratory, Chapter Nine discusses the planning of material requirements and supply in manufacturing, and Chapter Ten deals with the special problems of process manufacturing. While these topics are more specialized, they are included because their structures are not well understood even in the industries to which they apply, and because they introduce some very interesting modeling problems. Because they are specialized, each chapter begins with an introductory description of the situation the models will portray.
The final two chapters return to topics of more general interest: Chapter Eleven discusses the management of documents—a particularly knotty problem, as the chapter explains. Chapter Twelve identifies model elements that were components of the models that appeared in the previous chapters. This introduces the idea that even our data model patterns contain patterns within them. This final chapter concludes the book with a single model that takes the book’s premises to extremes, presenting a model that, with seven entities, appears to model everything.