Data Modeling Fundamentals: A Practical Guide for IT Professionals Book

Preface     xvii
Acknowledgments     xxi
Introduction to Data Modeling     1
Data Modeling: An Overview     3
Chapter Objectives     3
Data Model Defined     4
What Is a Data Model?     5
Why Data Modeling?     6
Who Performs Data Modeling?     9
Information Levels     10
Classification of Information Levels     11
Data Models at Information Levels     13
Conceptual Data Modeling     17
Data Model Components     18
Data Modeling Steps     20
Data Model Quality     26
Significance of Data Model Quality     27
Data Model Characteristics     27
Ensuring Data Model Quality     28
Data System Development     29
Data System Development Life Cycle     29
Roles and Responsibilities     33
Modeling the Information Requirements     33
Applying Agile Modeling Principles     34
Data Modeling Approaches and Trends     35
Data Modeling Approaches     36
Modeling for Data Warehouse     38
Other Modeling Trends     39
ChapterSummary     41
Review Questions     41
Methods, Techniques, and Symbols     43
Chapter Objectives     43
Data Modeling Approaches     44
Semantic Modeling     44
Relational Modeling     45
Entity-Relationship Modeling     46
Binary Modeling     46
Methods and Techniques     47
Peter Chen (E-R) Modeling     48
Information Engineering     50
Integration Definition for Information Modeling     51
Richard Barker's Model     53
Object-Role Modeling     55
eXtensible Markup Language     57
Summary and Comments     60
Unified Modeling Language     61
Data Modeling Using UML     61
UML in the Development Process     64
Chapter Summary     68
Review Questions     68
Data Modeling Fundamentals     71
Anatomy of a Data Model     73
Chapter Objectives     73
Data Model Composition     74
Models at Different Levels     74
Conceptual Model: Review Procedure     76
Conceptual Model: Identifying Components     77
Case Study     81
Description     81
E-R Model     84
UML Model     87
Creation of Models     89
User Views     90
View Integration     92
Entity Types     96
Specialization/Generalization     98
Relationships     98
Attributes     100
Identifiers     101
Review of the Model Diagram     103
Logical Model: Overview     104
Model Components     104
Transformation Steps     107
Relational Model     109
Physical Model: Overview     111
Model Components     111
Transformation Steps     112
Chapter Summary     113
Review Questions     113
Objects or Entities in Detail     115
Chapter Objectives     115
Entity Types or Object Sets     116
Comprehensive Definition     116
Identifying Entity Types     120
Homonyms and Synonyms     125
Category of Entity Types     127
Exploring Dependencies     130
Dependent or Weak Entity Types     131
Classifying Dependencies     132
Representation in the Model     133
Generalization and Specialization     134
Why Generalize or Specialize?     136
Supertypes and Subtypes     137
Generalization Hierarchy     138
Inheritance of Attributes     140
Inheritance of Relationships     140
Constraints     141
Rules Summarized     144
Special Cases and Exceptions     144
Recursive Structures     145
Conceptual and Physical     145
Assembly Structures     147
Entity Type Versus Attribute     148
Entity Type Versus Relationship     148
Modeling Time Dimension     149
Categorization     150
Entity Validation Checklist     153
Completeness     153
Correctness     154
Chapter Summary     155
Review Questions     155
Attributes and Identifiers in Detail     157
Chapter Objectives     157
Attributes     158
Properties or Characteristics     158
Attributes as Data     161
Attribute Values     162
Names and Descriptions      163
Attribute Domains     164
Definition of a Domain     164
Domain Information     165
Attribute Values and Domains     166
Split Domains     167
Misrepresented Domains     167
Resolution of Mixed Domains     168
Constraints for Attributes     169
Value Set     169
Range     170
Type     170
Null Values     170
Types of Attributes     171
Single-Valued and Multivalued Attributes     171
Simple and Composite Attributes     171
Attributes with Stored and Derived Values     172
Optional Attributes     173
Identifiers or Keys     175
Need for Identifiers     175
Definitions of Keys     175
Guidelines for Identifiers     176
Key in Generalization Hierarchy     177
Attribute Validation Checklist     178
Completeness     178
Correctness     179
Chapter Summary     180
Review Questions     180
Relationships in Detail     183
Chapter Objectives     183
Relationships      184
Associations     184
Relationship: Two-Sided     186
Relationship Sets     187
Double Relationships     187
Relationship Attributes     189
Degree of Relationships     190
Unary Relationship     191
Binary Relationship     191
Ternary Relationship     193
Quaternary Relationship     193
Structural Constraints     194
Cardinality Constraint     195
Participation Constraint     198
Dependencies     200
Entity Existence     200
Relationship Types     201
Identifying Relationship     202
Nonidentifying Relationship     204
Maximum and Minimum Cardinalities     204
Mandatory Conditions: Both Ends     206
Optional Condition: One End     206
Optional Condition: Other End     207
Optional Conditions: Both Ends     208
Special Cases     209
Gerund     209
Aggregation     210
Access Pathways     211
Design Issues     215
Relationship or Entity Type?     215
Ternary Relationship or Aggregation?     216
Binary or N-ary Relationship?     216
One-to-One Relationships     217
One-to-Many Relationships     219
Circular Structures     219
Redundant Relationships     221
Multiple Relationships     221
Relationship Validation Checklist     222
Completeness     223
Correctness     224
Chapter Summary     225
Review Questions     225
Data Model Implementation     227
Data Modeling to Database Design     229
Chapter Objectives     229
Relational Model: Fundamentals     231
Basic Concepts     231
Structure and Components     233
Data Integrity Constraints     238
Transition to Database Design     242
Design Approaches     243
Conceptual to Relational Model     243
Traditional Method     244
Evaluation of Design Methods     245
Model Transformation Method     246
The Approach     246
Mapping of Components     249
Entity Types to Relations     250
Attributes to Columns     250
Identifiers to Keys     252
Transformation of Relationships     252
Transformation Summary     267
Chapter Summary     269
Review Questions     269
Data Normalization     271
Chapter Objectives     271
Informal Design     272
Forming Relations from Requirements     272
Potential Problems     273
Update Anomaly     275
Deletion Anomaly     275
Addition Anomaly     276
Normalization Methodology     276
Strengths of the Method     277
Application of the Method     277
Normalization Steps     277
Fundamental Normal Forms     278
First Normal Form     278
Second Normal Form     279
Third Normal Form     281
Boyce-Codd Normal Form     284
Higher Normal Forms     285
Fourth Normal Form     286
Fifth Normal Form     287
Domain-Key Normal Form     288
Normalization Summary     290
Review of the Steps     290
Normalization as Verification     291
Chapter Summary     292
Review Questions      292
Modeling for Decision-Support Systems     295
Chapter Objectives     295
Decision-Support Systems     296
Need for Strategic Information     296
History of Decision-Support Systems     297
Operational Versus Informational Systems     299
System Types and Modeling Methods     299
Data Warehouse     301
Data Warehouse Defined     301
Major Components     302
Data Warehousing Applications     305
Modeling: Special Requirements     305
Dimensional Modeling     308
Dimensional Modeling Basics     309
STAR Schema     312
Snowflake Schema     318
Families of STARS     321
Transition to Logical Model     322
OLAP Systems     325
Features and Functions of OLAP     325
Dimensional Analysis     326
Hypercubes     328
OLAP Implementation Approaches     330
Data Modeling for OLAP     332
Data Mining Systems     334
Basic Concepts     334
Data Mining Techniques     338
Data Preparation and Modeling     339
Data Preprocessing     339
Data Modeling     341
Chapter Summary     342
Review Questions     343
Practical Approach to Data Modeling     345
Ensuring Quality in the Data Model     347
Chapter Objectives     347
Significance of Quality     348
Why Emphasize Quality?     348
Good and Bad Models     349
Approach to Good Modeling     351
Quality of Definitions     351
Importance of Definitions     352
Aspects of Quality Definitions     353
Correctness     353
Completeness     354
Clearness     357
Format     358
Checklists     358
High-Quality Data Model     360
Meaning of Data Model Quality     360
Quality Dimensions     361
What Is a High-Quality Model?     363
Benefits of High-Quality Models     364
Quality Assurance Process     365
Aspects of Quality Assurance     365
Stages of Quality Assurance Process     366
Data Model Review     369
Data Model Assessment     370
Chapter Summary      373
Review Questions     373
Agile Data Modeling in Practice     375
Chapter Objectives     375
The Agile Movement     376
How It Got Started     377
Principles of Agile Development     378
Philosophies     378
Generalizing Specialists     379
Agile Modeling     379
What Is Agile Modeling?     380
Basic Principles     380
Auxiliary Principles     381
Practicing Agile Modeling     381
Primary Practices     381
Additional Practices     382
Role of Agile DBA     383
Agile Documentation     383
Recognizing an Agile Model     384
Feasibility     384
Evolutionary Data Modeling     385
Traditional Approach     385
Need for Flexibility     386
Nature of Evolutionary Modeling     386
Benefits     387
Chapter Summary     388
Review Questions     388
Data Modeling: Practical Tips     391
Chapter Objectives     391
Tips and Suggestions     392
Nature of Tips     392
How Specified     392
How to Use Them     392
Requirements Definition     393
Interviews     393
Group Sessions     394
Geographically Dispersed Groups     394
Documentation     395
Change Management     395
Notes for Modeling     396
Stakeholder Participation     396
Organizing Participation     397
User Liaison     397
Continuous Interaction     398
Multiple Sites     399
Iterative Modeling     399
Establishing Cycles     399
Determining Increments     400
Requirements: Model Interface     400
Integration of Partial Models     401
Special Cases     401
Legal Entities     402
Locations and Places     403
Time Periods     405
Persons     407
Bill-of-Materials     409
Conceptual Model Layout     409
Readability and Usability     409
Component Arrangement     410
Adding Texts     416
Visual Highlights     417
Logical Data Model     417
Enhancement Motivation     418
Easier Database Implementation     418
Performance Improvement     418
Storage Management     419
Enhanced Representation     419
Chapter Summary     421
Review Questions     421
Bibliography     423
Glossary     425
Index     433