Logical database design principles

Title:

Personal Author:

Garmany, John

Series:

Foundations of database design series

Publication Information:

Boca Raton, FL : Auerbach Publications, 2005

ISBN:

9780849318535

Subject Term:

Database design

Added Author:

Walker, Jeff

Clark, Terry

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010134633	QA76.9.D26 G37 2005	Open Access Book	Book	Searching... Unknown

Until now, almost all books on logical database design focused exclusively on relational design. However, modern database management systems have added powerful features that have driven a movement away from truly normalized database design. Logical Database Design Principles reflects these recent changes. The book begins by covering traditional logical design principles, followed by an analysis of the normalizing and modeling of data. It then examines designing for specific purposes, such as object-oriented databases, online transaction processing (OLTP), and data warehouses. As the text progresses, it moves from the purely logical into some physical design, as determined by how the features of modern databases are implemented.

Because this is a logical-design book, the authors attempt to make the examples database-neutral. Because various vendors implement features in different ways, this volume sometimes offers examples from a specific database management system. When necessary, it highlights a specific application, clearly demonstrating the concept being discussed.

1 Introduction to Logical Database Design	p. 1
Understanding a Database	p. 1
Database Architectures	p. 2
Relational Databases	p. 4
Creating the Database	p. 4
System Development Life Cycle (SDLC)	p. 5
Systems Planning: Assessment and Feasibility	p. 5
System Analysis: Requirements	p. 6
System Analysis: Requirements Checklist	p. 8
Models Tracking and Schedules	p. 8
Design Modeling	p. 9
Functional Decomposition Diagram	p. 10
Data Flow Diagrams	p. 11
Data Dictionary	p. 12
Logical Structures and Decision Trees	p. 14
System Design: Logical	p. 15
2 System Design and Implementation	p. 17
The ER Approach	p. 17
Entities and Entity Types	p. 18
Attribute Domains	p. 20
Attributes	p. 20
Set-Valued Attributes	p. 20
Weak Entities	p. 22
Constraints	p. 23
Key Constraints: Primary	p. 23
Key Constraints: Foreign	p. 24
Lookup Tables and Consistency	p. 25
Modeling Approaches	p. 26
Relationships	p. 26
Cardinality	p. 29
Schemas	p. 31
Implementation: Converting the ERD	p. 32
Specifications and Documentation	p. 34
3 Converting the Logical Data Model	p. 35
Database Architecture	p. 35
SQL	p. 38
DDL Commands	p. 38
Data Retrieval	p. 45
DML Statements and Implicit Cursors	p. 46
Select Statements	p. 47
Cartesian Product	p. 49
DML: Insert Commands	p. 50
DML: Update Command	p. 51
DML: Delete Statements	p. 52
Transaction Commands	p. 53
DCL Commands	p. 54
4 Formal Data Normalization	p. 55
Definitions of Normal Forms	p. 57
First Normal Form	p. 57
Second Normal Form	p. 57
Third Normal Form	p. 57
Boyce-Codd Normal Form	p. 58
Fourth Normal Form	p. 58
Fifth Normal Form	p. 58
Introduction to Relational Algebra	p. 59
Comparison Operations and Logical Operators	p. 65
Applying Normal Forms	p. 66
First Normal Form	p. 68
Second Normal Form	p. 68
Third Normal Form	p. 70
Boyce-Codd Normal Form	p. 71
Fourth Normal Form	p. 71
Fifth Normal Form	p. 71
Summary	p. 71
5 Data Denormalization	p. 73
Historical Perspective on Disk Costs	p. 73
The Importance of Database Performance to the Logical Model	p. 74
Introducing Data Redundancy: Size versus Volatility	p. 75
The Theory of Dr. Ralph Kimball	p. 76
Pre-Joining Entities Together	p. 76
Pre-Aggregating Summary Information	p. 78
Non-First Normal Form Entities	p. 79
Horizontal and Vertical Partitioning for Performance	p. 79
Summary	p. 80
6 Object-Oriented Design	p. 83
Object-Oriented Terminology	p. 85
Classes	p. 85
Objects	p. 86
Messages	p. 86
Abstract Classes	p. 86
Encapsulation	p. 86
Inheritance	p. 87
Polymorphism	p. 87
Containment	p. 88
Extensibility	p. 88
Object Identity	p. 88
Transparent Persistence	p. 90
Storage and Access of Objects	p. 90
Object-Oriented Design	p. 91
Object-Oriented Analysis	p. 91
Different Models for Object Analysis	p. 91
The Rumbaugh Method	p. 93
The Booch Method	p. 93
The Coad-Yourdon Method	p. 93
The Shlaer-Mellor Method	p. 94
The Unified Modeling Language	p. 94
Creating the Object Model	p. 95
Methods and Database Objects	p. 98
Summary	p. 100
7 Object-Relational Design	p. 101
Advantages of Object-Relational Databases	p. 102
Atomic, Normalized Data	p. 102
Ad hoc Queries	p. 102
Object Types	p. 103
Large Objects	p. 105
Collections	p. 107
Arrays	p. 107
Nested Tables	p. 108
Object Views	p. 110
Using Logical Pointers	p. 111
Comparison of Object-Oriented and Object-Relational Databases	p. 115
Creating the Object-Relational Design	p. 116
Logical Object Pointers	p. 117
Automated Tools	p. 118
Summary	p. 119
8 Designing Replicated Databases	p. 121
Manual Replication Techniques	p. 122
Standby Database	p. 123
Replication Using Triggers	p. 124
Replication Using Views	p. 124
One-Way Replication	p. 125
Writeable Replication	p. 125
Updateable Replication	p. 126
The Push-Pull Method	p. 126
The Multi-Master Method	p. 127
The Streams Method	p. 129
What Are Conflicts?	p. 130
Conflict Avoidance	p. 131
Database Conflict Resolution	p. 132
Which Form of Replication is Right for You?	p. 133
Planning Your Replication Schema	p. 135
Primary Keys	p. 135
Foreign Keys	p. 135
Indexes	p. 136
Denormalization	p. 136
Moving Large Datasets	p. 136
Resynching Data	p. 137
Summary	p. 137
9 Design of the OLTP Database	p. 139
Designing for Online Transaction Processing	p. 139
Normalization	p. 140
Data Storage	p. 141
Database Data Cache Efficiency	p. 142
Data Growth	p. 144
SQL Reuse	p. 146
Database Locking and Waiting	p. 148
Deadlocks	p. 149
Rollbacks	p. 149
Indexing	p. 150
Primary Keys	p. 151
Table with Three or More Columns	p. 151
Multiple Indexes with the Most Restrictive Lead Columns	p. 151
Large Multi-Column Indexes	p. 152
Organizing Tables as Indexes	p. 152
Summary	p. 153
10 Design of Data Warehouses and Decision Support System Databases	p. 155
What Is a Data Warehouse?	p. 155
OLAP, MOLAP, and ROLAP	p. 156
Using an Operational Database as a Data Warehouse	p. 157
Gathering Data	p. 158
Staging and Processing Data	p. 158
Loading and Unloading Data	p. 159
Data Marts	p. 161
Designing the Data Warehouse	p. 161
Data Granularity	p. 162
Partitioning Data	p. 162
Which Attribute to Partition On	p. 163
Where to Partition	p. 164
Use of Keys	p. 167
Normalization	p. 168
Dimensional Modeling	p. 168
Pre-Aggregation	p. 169
Protect the Data	p. 171
Summary	p. 171
Index	p. 173

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