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E-raamat: Database Modeling and Design: Logical Design

(Senior Technical Staff Member and Development Manager, IBM, Toronto, Canada), (Ubiquiti Inc., Ann Arbor, MI), (Univ of Mich, ), (Professor, Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor, USA)
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Database Modeling and Design, Fourth Edition, the extensively revised edition of the classic logical database design reference, explains how you can model and design your database application in consideration of new technology or new business needs. It is an ideal text for a stand-alone data management course focused on logical database design, or a supplement to an introductory text for introductory database management.

This book features clear explanations, lots of terrific examples and an illustrative case, and practical advice, with design rules that are applicable to any SQL-based system. The common examples are based on real-life experiences and have been thoroughly class-tested. The text takes a detailed look at the Unified Modeling Language (UML-2) as well as the entity-relationship (ER) approach for data requirements specification and conceptual modeling - complemented with examples for both approaches. It also discusses the use of data modeling concepts in logical database design; the transformation of the conceptual model to the relational model and to SQL syntax; the fundamentals of database normalization through the fifth normal form; and the major issues in business intelligence such as data warehousing, OLAP for decision support systems, and data mining. There are examples for how to use the most popular CASE tools to handle complex data modeling problems, along with exercises that test understanding of all material, plus solutions for many exercises. Lecture notes and a solutions manual are also available.

This edition will appeal to professional data modelers and database design professionals, including database application designers, and database administrators (DBAs); new/novice data management professionals, such as those working on object oriented database design; and students in second courses in database focusing on design.

Arvustused

"An explicit presentation on Business Intelligence is a major strength of this book. For beginners, there is an elegant presentation on SQL in the appendix and the book is supplemented by a detailed glossary. Exercises, examples and solutions constitute an important part of this book. This book is useful reading for both beginners and advanced users as the contents integrate elements that would address various audiences at different levels." --P. Pichappan, Department of Information Science, Annamalai University, India

Preface xv
Introduction
1(12)
Data and Database Management
2(1)
The Database Life Cycle
3(5)
Conceptual Data Modeling
8(3)
Summary
11(1)
Literature Summary
11(2)
The Entity-Relationship Model
13(20)
Fundamental ER Constructs
13(10)
Basic Objects: Entities, Relationships, Attributes
13(3)
Degree of a Relationship
16(2)
Connectivity of a Relationship
18(1)
Attributes of a Relationship
19(1)
Existence of an Entity in a Relationship
19(1)
Alternative Conceptual Data Modeling Notations
20(3)
Advanced ER Constructs
23(7)
Generalization: Supertypes and Subtypes
23(2)
Aggregation
25(1)
Ternary Relationships
25(3)
General n-ary Relationships
28(1)
Exclusion Constraint
29(1)
Referential Integrity
30(1)
Summary
30(1)
Literature Summary
31(2)
The Unified Modeling Language (UML)
33(20)
Class Diagrams
34(12)
Basic Class Diagram Notation
35(2)
Class Diagrams for Database Design
37(6)
Example from the Music Industry
43(3)
Activity Diagrams
46(4)
Activity Diagram Notation Description
46(2)
Activity Diagrams for Workflow
48(2)
Rules of Thumb for UML Usage
50(1)
Summary
51(1)
Literature Summary
51(2)
Requirements Analysis and Conceptual Data Modeling
53(30)
Introduction
53(1)
Requirements Analysis
54(1)
Conceptual Data Modeling
55(11)
Classify Entities and Attributes
56(1)
Identify the Generalization Hierarchies
57(1)
Define Relationships
58(3)
Example of Data Modeling: Company Personnel and Project Database
61(5)
View Integration
66(8)
Preintegration Analysis
67(1)
Comparison of Schemas
68(1)
Conformation of Schemas
68(1)
Merging and Restructuring of Schemas
69(1)
Example of View Integration
69(5)
Entity Clustering for ER Models
74(7)
Clustering Concepts
75(1)
Grouping Operations
76(2)
Clustering Technique
78(3)
Summary
81(1)
Literature Summary
82(1)
Transforming the Conceptual Data Model to SQL
83(24)
Transformation Rules and SQL Constructs
83(20)
Binary Relationships
85(5)
Binary Recursive Relationships
90(2)
Ternary and n-ary Relationships
92(9)
Generalization and Aggregation
101(2)
Multiple Relationships
103(1)
Weak Entities
103(1)
Transformation Steps
103(3)
Entity Transformation
104(1)
Many-to-Many Binary Relationship Transformation
104(1)
Ternary Relationship Transformation
105(1)
Example of ER-to-SQL Transformation
105(1)
Summary
106(1)
Literature Summary
106(1)
Normalization
107(32)
Fundamentals of Normalization
107(9)
First Normal Form
109(1)
Superkeys, Candidate Keys, and Primary Keys
109(2)
Second Normal Form
111(2)
Third Normal Form
113(2)
Boyce-Codd Normal Form
115(1)
The Design of Normalized Tables: A Simple Example
116(2)
Normalization of Candidate Tables Derived from ER Diagrams
118(4)
Determining the Minimum Set of 3NF Tables
122(5)
Fourth and Fifth Normal Forms
127(10)
Multivalued Dependencies
127(2)
Fourth Normal Form
129(3)
Decomposing Tables to 4NF
132(1)
Fifth Normal Form
133(4)
Summary
137(1)
Literature Summary
138(1)
An Example of Logical Database Design
139(8)
Requirements Specification
139(2)
Design Problems
140(1)
Logical Design
141(4)
Summary
145(2)
Business Intelligence
147(40)
Data Warehousing
148(18)
Overview of Data Warehousing
148(4)
Logical Design
152(14)
Online Analytical Processing (OLAP)
166(12)
The Exponential Explosion of Views
167(2)
Overview of OLAP
169(1)
View Size Estimation
170(3)
Selection of Materialized Views
173(3)
View Maintenance
176(1)
Query Optimization
177(1)
Data Mining
178(7)
Forecasting
179(2)
Text Mining
181(4)
Summary
185(1)
Literature Summary
186(1)
CASE Tools for Logical Database Design
187(26)
Introduction to the CASE Tools
188(3)
Key Capabilities to Watch For
191(1)
The Basics
192(4)
Generating a Database from a Design
196(3)
Database Support
199(1)
Collaborative Support
200(1)
Distributed Development
201(1)
Application Life Cycle Tooling Integration
202(2)
Design Compliance Checking
204(2)
Reporting
206(1)
Modeling a Data Warehouse
207(2)
Semi-Structured Data, XML
209(2)
Summary
211(1)
Literature Summary
211(2)
Appendix: The Basics of SQL 213(18)
Glossary 231(8)
References 239(10)
Exercises 249(10)
Solutions to Selected Exercises 259(4)
About the Authors 263(2)
Index 265


Toby J. Teorey is a professor in the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor. He received his B.S. and M.S. degrees in electrical engineering from the University of Arizona, Tucson, and a Ph.D. in computer sciences from the University of Wisconsin, Madison. He was general chair of the 1981 ACM SIGMOD Conference and program chair for the 1991 Entity-Relationship Conference. Professor Teoreys current research focuses on database design and data warehousing, OLAP, advanced database systems, and performance of computer networks. He is a member of the ACM and the IEEE Computer Society. Sam Lightstone is a Senior Technical Staff Member and Development Manager with IBMs DB2 product development team. His work includes numerous topics in autonomic computing and relational database management systems. He is cofounder and leader of DB2s autonomic computing R&D effort. He is Chair of the IEEE Data Engineering Workgroup on Self Managing Database Systems and a member of the IEEE Computer Society Task Force on Autonomous and Autonomic Computing. In 2003 he was elected to the Canadian Technical Excellence Council, the Canadian affiliate of the IBM Academy of Technology. He is an IBM Master Inventor with over 25 patents and patents pending; he has published widely on autonomic computing for relational database systems. He has been with IBM since 1991. Tom Nadeau is the founder of Aladdin Software (aladdinsoftware.com) and works in the area of data and text mining. He received his B.S. degree in computer science and M.S. and Ph.D. degrees in electrical engineering and computer science from the University of Michigan, Ann Arbor. His technical interests include data warehousing, OLAP, data mining and machine learning. He won the best paper award at the 2001 IBM CASCON Conference. H.V. Jagadish is a professor in EE and CS at the University of Michigan, Ann Arbor, where he is part of the database group affiliated with the bioinformatics program and the Center for Computational Medicine and Bioinformatics. Prior to joining the Michigan faculty, he spent over a decade at AT&T Bell Laboratories as a research scientist where he became head of the Database division.