Data Modeling Essentials (eBook)

Graeme Simsion, Graham Witt (Autoren)

eBook Download: PDF

2004 | 3. Auflage
560 Seiten
Elsevier Science (Verlag)
978-0-08-048867-7 (ISBN)

Infos

Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at all levels. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management.

The third edition of this popular book retains its distinctive hallmarks of readability and usefulness, but has been given significantly expanded coverage and reorganized for greater reader comprehension. Authored by two leaders in the field, Data Modeling Essentials, Third Edition is the ideal reference for professionals and students looking for a real-world perspective.

? Thorough coverage of the fundamentals and relevant theory.
? Recognition and support for the creative side of the process.
? Expanded coverage of applied data modeling includes new chapters on logical and physical database design.
? New material describing a powerful technique for model verification.
? Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict.
? Extensive online component including course notes and other teaching aids (www.mkp.com).

UML diagrams now available! Visit the companion site for more details.

Click here to view a book review by Steve Hoberman!

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Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "e;the rules"e;. In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory- Recognition and support for the creative side of the process- Expanded coverage of applied data modeling includes new chapters on logical and physical database design- New material describing a powerful technique for model verification- Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict

Inhalt

Cover 1
Title Page 4
Copyright Page 5
Contents 8
Preface 24
Part I: The Basics 30
Chapter 1. What Is Data Modeling? 32
1.1 Introduction 32
1.2 A Data-Centered Perspective 32
1.3 A Simple Example 33
1.4 Design, Choice, and Creativity 35
1.5 Why Is the Data Model Important? 37
1.6 What Makes a Good Data Model? 39
1.7 Performance 44
1.8 Database Design Stages and Deliverables 45
1.9 Where Do Data Models Fit In? 20 49
1.10 Who Should Be Involved in Data Modeling? 52
1.11 Is Data Modeling Still Relevant? 53
1.12 Alternative Approaches to Data Modeling 58
1.13 Terminology 59
1.14 Where to from Here?„An Overview of Part I 60
1.15 Summary 61
Chapter 2. Basics of Sound Structure 62
2.1 Introduction 62
2.2 An Informal Example of Normalization 63
2.3 Relational Notation 65
2.4 A More Complex Example 66
2.5 Determining Columns 69
2.6 Repeating Groups and First Normal Form 72
2.7 Second and Third Normal Forms 76
2.8 Definitions and a Few Refinements 82
2.9 Choice, Creativity, and Normalization 89
2.10 Terminology 91
2.11 Summary 92
Chapter 3. The Entity-Relationship Approach 94
3.1 Introduction 94
3.2 A Diagrammatic Representation 94
3.3 The Top-Down Approach: Entity-Relationship Modeling 101
3.4 Entity Classes 105
3.5 Relationships 111
3.6 Attributes 133
3.7 Myths and Folklore 134
3.8 Creativity and E-R Modeling 135
3.9 Summary 138
Chapter 4. Subtypes and Supertypes 140
4.1 Introduction 140
4.2 Different Levels of Generalization 140
4.3 Rules versus Stability 142
4.4 Using Subtypes and Supertypes 144
4.5 Subtypes and Supertypes as Entity Classes 145
4.6 Diagramming Conventions 146
4.7 Definitions 148
4.8 Attributes of Supertypes and Subtypes 148
4.9 Nonoverlapping and Exhaustive 149
4.10 Overlapping Subtypes and Roles 152
4.11 Hierarchy of Subtypes 156
4.12 Benefits of Using Subtypes and Supertypes 157
4.13 When Do We Stop Supertyping and Subtyping? 163
4.14 Generalization of Relationships 167
4.15 Theoretical Background 171
4.16 Summary 172
Chapter 5. Attributes and Columns 174
5.1 Introduction 174
5.2 Attribute Definition 175
5.3 Attribute Disaggregation: One Fact per Attribute 176
5.4 Types of Attributes 181
5.5 Attribute Names 195
5.6 Attribute Generalization 200
5.7 Summary 209
Chapter 6. Primary Keys and Identity 212
6.1 Basic Requirements and Trade-Offs 212
6.2 Basic Technical Criteria 214
6.3 Surrogate Keys 220
6.4 Structured Keys 223
6.5 Multiple Candidate Keys 230
6.6 Guidelines for Choosing Keys 231
6.7 Partially-Null Keys 233
6.8 Summary 235
Chapter 7. Extensions and Alternatives 236
7.1 Introduction 236
7.2 Extensions to the Basic E-R Approach 238
7.3 The Chen E-R Approach 245
7.4 Using UML Object Class Diagrams 249
7.5 Object Role Modeling 256
7.6 Summary 257
Part II: Putting It Together 258
Chapter 8. Organizing the Data Modeling Task 260
8.1 Data Modeling in the Real World 260
8.2 Key Issues in Project Organization 262
8.3 Roles and Responsibilities 267
8.4 Partitioning Large Projects 269
8.5 Maintaining the Model 271
8.6 Packaging It Up 277
8.7 Summary 278
Chapter 9. The Business Requirements 280
9.1 Purpose of the Requirements Phase 280
9.2 The Business Case 282
9.3 Interviews and Workshops 283
9.4 Riding the Trucks 287
9.5 Existing Systems and Reverse Engineering 288
9.6 Process Models 290
9.7 Object Class Hierarchies 290
9.8 Summary 299
Chapter 10. Conceptual Data Modeling 302
10.1 Designing Real Models 302
10.2 Learning from Designers in Other Disciplines 304
10.3 Starting the Modeling 305
10.4 Patterns and Generic Models 306
10.5 Bottom-Up Modeling 314
10.6 Top-Down Modeling 317
10.7 When the Problem Is Too Complex 317
10.8 Hierarchies, Networks, and Chains 319
10.9 One-to-One Relationships 324
10.10 Developing Entity Class Definitions 329
10.11 Handling Exceptions 330
10.12 The Right Attitude 331
10.13 Evaluating the Model 334
10.14 Direct Review of Data Model Diagrams 335
10.15 Comparison with the Process Model 337
10.16 Testing the Model with Sample Data 337
10.17 Prototypes 338
10.18 The Assertions Approach 338
10.19 Summary 348
Chapter 11. Logical Database Design 350
11.1 Introduction 350
11.2 Overview of the Transformations Required 351
11.3 Table Specification 354
11.4 Basic Column Definition 363
11.5 Primary Key Specification 370
11.6 Foreign Key Specification 371
11.7 Table and Column Names 383
11.8 Logical Data Model Notations 384
11.9 Summary 386
Chapter 12. Physical Database Design 388
12.1 Introduction 388
12.2 Inputs to Database Design 390
12.3 Options Available to the Database Designer 391
12.4 Design Decisions Which Do Not Affect Program Logic 392
12.5 Crafting Queries to Run Faster 401
12.6 Logical Schema Decisions 403
12.7 Views 413
12.8 Summary 415
Part III: Advanced Topics 418
Chapter 13. Advanced Normalization 420
13.1 Introduction 420
13.2 Introduction to the Higher Normal Forms 421
13.3 Boyce-Codd Normal Form 423
13.4 Fourth Normal Form (4NF) and Fifth Normal Form (5NF) 427
13.5 Beyond 5NF: Splitting Tables Based on Candidate Keys 436
13.6 Other Normalization Issues 437
13.7 Advanced Normalization in Perspective 444
13.8 Summary 445
Chapter 14. Modeling Business Rules 446
14.1 Introduction 446
14.2 Types of Business Rules 447
14.3 Discovery and Verification of Business Rules 449
14.4 Documentation of Business Rules 451
14.5 Implementing Business Rules 456
14.6 Rules on Recursive Relationships 475
14.7 Summary 479
Chapter 15. Time-Dependent Data 480
15.1 The Problem 480
15.2 When Do We Add the Time Dimension? 481
15.3 Audit Trails and Snapshots 481
15.4 Sequences and Versions 491
15.5 Handling Deletions 492
15.6 Archiving 492
15.7 Modeling Time-Dependent Relationships 493
15.8 Date Tables 498
15.9 Temporal Business Rules 498
15.10 Changes to the Data Structure 502
15.11 Putting It into Practice 502
15.12 Summary 503
Chapter 16. Modeling for Data Warehouses Data Marts 504
16.1 Introduction 504
16.2 Characteristics of Data Warehouses and Data Marts 507
16.3 Quality Criteria for Warehouse and Mart Models 509
16.4 The Basic Design Principle 512
16.5 Modeling for the Data Warehouse 513
16.6 Modeling for the Data Mart 517
16.7 Summary 525
Chapter 17. Enterprise Data Models and Data Management 528
17.1 Introduction 528
17.2 Data Management 529
17.3 Classification of Existing Data 532
17.4 A Target for Planning 533
17.5 A Context for Specifying New Databases 535
17.6 Guidance for Database Design 537
17.7 Input to Business Planning 537
17.8 Specification of an Enterprise Database 538
17.9 Characteristics of Enterprise Data Models 540
17.10 Developing an Enterprise Data Model 541
17.11 Choice, Creativity, and Enterprise Data Models 545
17.12 Summary 546
Further Reading 548

Produkt-Details

• Erscheint lt. Verlag: 3.12.2004
• Sprache: englisch
• Themenwelt: Sachbuch/Ratgeber
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Mathematik / Informatik ► Informatik ► Software Entwicklung
• Themenwelt: Informatik ► Weitere Themen ► Hardware
• Themenwelt: Sozialwissenschaften ► Kommunikation / Medien ► Buchhandel / Bibliothekswesen
• ISBN-10: 0-08-048867-6 / 0080488676
• ISBN-13: 978-0-08-048867-7 / 9780080488677