data modelling

Data ModelingA Beginners Guide

Andy Oppel

TECHNISCHE

INFORMATIONSBtBUOTHEK

UNIVERSITATSBiBLIOTHEK

HANNOVER

McGravuHill

New York Chicago San FranciscoLisbon London Madrid Mexico CityMilan New Delhi San Juan

Seoul Singapore Sydney Toronto

Contents

ACKNOWLEDGMENTS xvii

INTRODUCTION xix

PART I Data Modeling Concepts

1 Introduction to Data Modeling 3Data-Centric Design 4Anatomy of a Data Model 6

Layers of Data Abstraction 6Types ofData Models 8

Importance of Data Modeling 12Documentation of Business Rules 12

Visualization 12

Illustration of Alternatives 13

Foundation for Future Expansion 13Promotion of Common and Standard Structures 13

Provisions for Automation 13

Measures of a Good Data Model 14

Enforcement of Business Rules 14

Flexible and Adaptable 15

ix

X Dafp Modeling: A Beginner's .Guide

Easily Understood 15Balanced Perspective 15Promotion of Data Reusability 16Data Integration 16

How Data Models Fit Into Application Development 16

Process-Oriented Methodologies 16

Data-Oriented Methodologies 17

Hybrid Methodologies 17

Object-Oriented Methodologies 17

Prototyping Methodologies 17

Agile Methodologies 18Data Modeling Participants 18

Try This 1 -1: Refining a Conceptual Model 19

Chapter 1 SelfTest 20

2 Relational Model Components 23

Conceptual and Logical Model Components 24Entities 25

Attributes 30

Relationships 32Business Rules 39

Physical Model Components 39Tables 39

Columns and Data Types 41Constraints 43

Integrity Constraints 46Views 48

Try This 2-1: Conceptual Model Modification 48Chapter 2 SelfTest 50

3 Data and Process Modeling S3Data Model Diagramming Alternatives 54

ERD Formats 54

Representing Supertypes and Subtypes 60Guidelines for Drawing ERDs 63

Process Models 63The Flowchart 64The Function Hierarchy Diagram 66The Swim Lane Diagram 67The Data Flow Diagram 68

Contents xi

Unified Modeling Language (UML) 70UML Class Diagrams 70

Other UML Diagrams 72

Relating Entities and Processes 73

Try This 3-1: Drawing a Conceptual Model with Nested Subtypes 75

Chapter 3 Self Test 76

4 Organizing Database Project Work 81

The Traditional Life Cycle 82

Planning 84

Requirements Gathering 85

Conceptual Design 88

Logical Design 89

Physical Design 89

Construction 90

Implementation and Rollout 90

Ongoing Support 91

Nontraditional Life Cycles 92

Prototyping 92

Rapid Application Development 93

The Project Triangle 93

Try This 4-1: Project Database Management Tasks 94


PART II Data Modeling Details

5 Conceptual Data Modeling 101

The Conceptual Modeling Process 102

Preparation 102

Solution Design 105

What Differentiates Conceptual Modeling from Logical Modeling? 105

Creating the Model 106

Generic Models and Patterns 106

Roles vs. Subtypes 109

Dealing with Hierarchies, Networks, and Linked Lists 113

Bottom Up vs. Top Down Modeling 118

Subject Areas 122

Evaluating the Model 123

What Makes a Good Conceptual Model? 123

Try This 5-1: Conceptual Model for International Addresses 124


xii Data Modeling: A Beginner's.Guide

6 Logical Database Design Using Normalization 127The Need for Normalization 130

Insert Anomaly 130Delete Anomaly 130

Update Anomaly 131

Applying the Normalization Process 131

Choosing a Primary Key 133First Normal Form: Eliminating Repeating Data 135

Second Normal Form: Eliminating Partial Dependencies 137Third Normal Form: Eliminating Transitive Dependencies 139

Denormalization 142

Practice Problems 142

Try This 6-1: UTLAAcademic Tracking 143

The User Views 143

Try This 6-2: Computer Books Company 146

The User Views 146


7 Beyond Third Normal Form 151

Advanced Normalization 152

Boyce-Codd Normal Form 152Fourth Normal Form 155

Fifth Normal Form 157

Domain-Key Normal Form (DKNF) 158Resolving Supertypes and Subtypes 158Generalizing Attributes 162Alternatives for Reference Data 166

Common Code Structures 166

Crosswalk Tables 167

Language Translation Tables 168

Try This 7-1: Complex Logical Data Model 169Chapter 7 Self Test 171

8 Physical Database Design 173The Physical Design Process 174

Designing Tables 176

Try This 8-1: Drawing a Physical Data Model 182

Implementing Supertypes and Subtypes 183Naming Conventions 186

Integrating Business Rules and Data Integrity 189NOT NULL Constraints 191

Primary Key Constraints 191

Contents xiii

Referential (Foreign Key) Constraints 191

Unique Constraints 192Check Constraints 193

Data Types, Precision, and Scale 193

Triggers 194

Adding Indexes for Performance 194

Designing Views 196

Try This 8-2: Mapping a Logical Model to a Physical Database Design 198


PART III Design Alternatives

9 Alternatives for Incorporating Business Rules 205

The Anatomy of a Business Rule 206The Origin of Business Rules 207

Implementing Business Rules in Data Models 207

Implementing Terms 207

Implementing Facts 209

Implementing Derivations 210

Limitations on Implementing Business Rules in Data Models 211

Implementing Constraints 211Constraints That Cannot Be Shown in Entity Relationship Models 212

Functional Classification of Business Rules 214

Definitional Rules 214

Data Validation Rules 214

Data Derivation Rules 215

Cardinality Rules 215

Referential Integrity Rules 215

Process Rules 215

Try This 9-1: Modeling Business Rules 216


10 Alternatives for Handling Temporal Data 219

Temporal Data Structures 220When Does Time Matter? 220

Adding History to Data Structures 221

Processing Rules for History 228

Handling Deletions 228

Calendar Data Structures 230

Business Rules for Temporal Data 231

Try This 10-1: Adding History to Data Structures 233


xiv Data Modeling:. A Beginner's .Guide.

11 Modeling for Analytical Databases 237

Data Warehouses 239

OLTP Systems Compared with Data Warehouse Systems 240Data Warehouse Architecture 240

Data Marts 245

Modeling Analytical Data Structures 247OLAP Database Requirements 247Data Warehouse Modeling 248Data Mart Modeling 250

Loading Data into Analytical Databases 257The Extract Process 258The Transform Process 258The Load Process 259

TryThis 11-1: Design Star SchemaFact andDimension Tables 259Chapter 11 Self Test 261

12 Enterprise Data Modeling 265

Enterprise Data Management 266The Case for Data Management 266Alternatives to Centralized Data Management 267

The Enterprise Data Model 268What Is an Enterprise Data Model? 268The Anatomy of an Enterprise Data Model 269Building an Enterprise Data Model 272

TryThis 12-1: Enterprise Conceptual Model Development 274Chapter 12 Self Test 274

PART IV Appendixes

A Answers to Self Tests 279

B Solutions to Try This Exercises 313TryThis 1-1: Refining a Conceptual Model 314Try This 2-1: Conceptual Model Modification 315

Try This 3-1: Drawing a Conceptual Model with Nested Subtypes 316Try This 4-1: The Database Life Cycle 317

Try This 5-1: Conceptual Model for International Addresses 318

Try This 6-1: UTLA Academic Tracking 319Try This 6-2: Computer Books Company 322Try This 7-1: Complex Logical DataModel 324

Try This 8-1: Drawing a Physical Data Model 325

Content? xv

Try This 8-2: Mapping a Logical Model to a Physical Database Design 326

Try This 9-1: Modeling Business Rules 326

Try This 10-1: Adding History to Data Structures 327

Try This 11-1: Design Star Schema Fact and Dimension Tables 328

Try This 12-1: Enterprise Conceptual Model Development 329

Index 331

data modelling

Documents