“A Developer’s Guide to Data Modeling for SQL Server explains the concepts and practice of data modeling with a clarity that makes the technology accessible to anyone building databases and data-driven applications. “Eric Johnson and Joshua Jones combine a deep understanding of the science of data modeling with the art that comes with years of experience. If you’re new to data modeling, or find the need to brush up on its concepts, this book is for you.” —Peter Varhol, Executive Editor, Redmond Magazine Model SQL Server Databases That Work Better, Do More, and Evolve More Smoothly Effective data modeling is essential to ensuring that your databases will perform well, scale well, and evolve to meet changing requirements. However, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic data modeling knowledge isn’t enough: models that don’t reflect SQL Server’s unique real-world strengths and weaknesses often lead to disastrous performance. A Developer’s Guide to Data Modeling for SQL Server is a practical, SQL Server-specific guide to data modeling for every developer, architect, and administrator. This book offers you invaluable start-to-finish guidance for designing new databases, redesigning existing SQL Server data models, and migrating databases from other platforms. You’ll begin with a concise, practical overview of the core data modeling techniques. Next, you’ll walk through requirements gathering and discover how to convert requirements into effective SQL Server logical models. Finally, you’ll systematically transform those logical models into physical models that make the most of SQL Server’s extended functionality. All of this book’s many examples are available for download from a companion Web site. This book enables you to Understand your data model’s physical elements, from storage to referential integrity Provide programmability via stored procedures, user-defined functions, triggers, and .NET CLR integration Normalize data models, one step at a time Gather and interpret requirements more effectively Learn an effective methodology for creating logical models Overcome modeling problems related to entities, attribute, data types, storage overhead, performance, and relationships Create physical models—from establishing naming guidelines through implementing business rules and constraints Use SQL Server’s unique indexing capabilities, and overcome their limitations Create abstraction layers that enhance security, extensibility, and flexibility

Table of Contents:
Preface                                            xv Acknowledgments                      xvii About the Authors                       xix PART I: Data Modeling Theory                                        1 Chapter 1: Data Modeling Overview                                3 Databases                4 Why a Sound Data Model Is Important               6 Data Consistency                6 The Process of Data Modeling             14 Summary                    21 Chapter 2:  Elements Used in Logical Data Models                          23 Entities              23 Attributes           24 Referential Integrity             32 Relationships               35 Relationship Types             35 Relationship Options           40 Cardinality             41 Using Subtypes and Supertypes               42 Supertypes and Subtypes Defined                 42 When to Use Subtype Clusters             44 Summary             44 Chapter 3: Physical Elements of Data Models                    45 Physical Storage               45 Referential Integrity            59 Programming            71 Implementing Supertypes and Subtypes           75 Summary            79 PART II: Business Requirements                                           95 Chapter 5: Requirements Gathering                                    97 Requirements Gathering Overview              98 Gathering Requirements Step by Step            98 Business Needs            111 Balancing Technical Limitations with Business Needs            112 Gathering Usage Data           112 Summary             116 Chapter 6: Interpreting Requirements            117 Mountain View Music                    117 Compiling Requirements Data           119 Determining Model Requirements               121 Determining the Business Rules             138 Requirements Documentation           141 Looking Ahead: The Business Review          143 Summary                  145 PART III: Creating the Logical Model                            147 Chapter 7: Creating the Logical Model                          149 Diagramming a Data Model           149 Using Requirements to Build the Model          157 Building the Model          164 Summary       170 Chapter 8: Common Data Modeling Problems                  171 Entity Problems       171 Attribute Problems     176 Relationship Problems      182 Summary         185 PART IV: Creating the Physical Model               187 Chapter 9: Creating the Physical Model with SQL Server              189 Naming Guidelines      189 Deriving the Physical Model      198 Implementing Business Rules in the Physical Model      211 Summary     219 Chapter 10: Indexing Considerations      221 Indexing Overview      221 Database Usage Requirements      230 Determining the Appropriate Indexes       233 Implementing Indexes in SQL Server            236 Summary            239 Chapter 11: Creating an Abstraction Layer in SQL Server                 241 What Is an Abstraction Layer?               241 Why Use an Abstraction Layer?           242 An Abstraction Layer’s Relationship to the Logical Model          245 An Abstraction Layer’s Relationship to Object-Oriented Programming       246 Implementing an Abstraction Layer     247 Summary      254 Appendix A: Sample Logical Model                              255 Appendix B: Sample Physical Model                            261 Appendix C: SQL Server 2008 Reserved Words             267 Appendix D: Recommended Naming Standards            269 Index              271