Beginning Relational Data Modeling

Front Cover
Apress, Nov 3, 2006 - Computers - 632 pages

Data storage design, and awareness of how data needs to be utilized within an organization, is of prime importance in ensuring that company data systems work efficiently. If you need to know how to capture the information needs of a business system in a relational database model, but don’t know where to start, then this is the book for you.

Beginning Relational Data Modeling, Second Edition will lead you step-by-step through the process of developing an effective logical data model for your relational database. No previous data modeling experience is even required. The authors infuse the book with concise, straightforward wisdom to explain a usually complex, jargon-filled discipline. And examples are based on their extensive experience modeling for real business systems.

 

Contents

Past and Present
1
CHAPTER
2
CHAPTER
4
CHAPTER
6
CHAPTER
8
CHAPTER
9
CHAPTER
10
CHAPTER
11
Starting the Logical Data Modeling
244
Modeling Card Movement Subject Area
275
Modeling the Event Subject Area
288
Performing Quality Assurance Checks
293
Summary
301
Transforming a Logical Model into a Physical Model
304
Creating Tables from Logical Categories
310
Examining Shadow Entities
321

CHAPTER
13
CHAPTER
14
CHAPTER
16
Summary
25
Introducing Relational Theory
27
Taking a Relational Approach to Data Modeling
33
Introducing Normalization
40
Introducing Denormalization
53
Understanding Relational Modeling Terminology
57
Summary
87
Graphical Syntax
89
EntityRelationship ER or Chen Diagramming
99
Summary
106
Introducing ObjectOriented Data Modeling
107
Supporting Object Models with Relational Databases
116
Example UML Transformation
123
Summary
129
Examining Levels of Analysis
131
Summary
160
How Data Models Fit Into Projects
163
Project Team Needs
169
Model Objective
183
Building a Conceptual Model
191
TopDown Approach
198
Summary
237
Building a Logical Model
239
Performing Quality Checks and Getting Extra Value
338
Summary
345
Designing a Physical Model Only
348
Summary
376
Introducing Dimensional Data Modeling
378
Introducing Star Schemas
382
Revisiting the Solitaire Model
388
Summary
420
ReverseEngineering a Data Model
422
Analyzing the Data
442
Using HistoricDescriptive Information
454
Finishing It Up
465
Communicating with the Model
468
Publishing Data Models
484
Improving Data Quality and Managing Documentation
488
Using the Data Model As a Knowledge Framework
501
Summary
515
Introducing Metadata Modeling
518
Exploring Data Modeling Working Practices
533
Exploring Data Modeling Working Practices
534
Understanding Data and Design
548
Closing Thoughts
560
Resources
563
APPENDIX B Glossary
569
INDEX
589
Copyright

Other editions - View all

Common terms and phrases

About the author (2006)

Sharon Allen has worked in the field of data analysis for 24 years: 10 as a business consumer of data and 14 as a data/database modeler/architect. She has had the opportunity to experience many diverse industries medical, aerospace, entertainment (Hollywood), manufacturing (toys, appliances, wet chemicals, metal part & assemblies), transportation, and food service and is currently working for American Honda Motors as a database architect. She plans to finish a master's degree in computer science and possibly teach at a local college.

Bibliographic information