Database modeling & design : logical design /

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Bibliographic Details
Author / Creator:Teorey, Toby J.
Edition:4th ed.
Imprint:San Francisco, CA : Elsevier Morgan Kaufmann Publishers, c2006.
Description:xviii, 275 p. : ill. ; 24 cm.
Language:English
Series:The Morgan Kaufmann series in data management systems
Morgan Kaufmann series in data management systems.
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/5751144
Hidden Bibliographic Details
Varying Form of Title:Database modeling and design
Other authors / contributors:Lightstone, Sam.
Nadeau, Tom.
ISBN:0126853525
Notes:Includes bibliographical references (p. 239-247) and index.
Table of Contents:
  • Preface
  • Chapter 1. Introduction
  • 1.1. Data and Database Management
  • 1.2. The Database Life Cycle
  • 1.3. Conceptual Data Modeling
  • 1.4. Summary
  • 1.5. Literature Summary
  • Chapter 2. The Entity-Relationship Model
  • 2.1. Fundamental ER Constructs
  • 2.1.1. Basic Objects: Entities, Relationships, Attributes
  • 2.1.2. Degree of a Relationship
  • 2.1.3. Connectivity of a Relationship
  • 2.1.4. Attributes of a Relationship
  • 2.1.5. Existence of an Entity in a Relationship
  • 2.1.6. Alternative Conceptual Data Modeling Notations
  • 2.2. Advanced ER Constructs
  • 2.2.1. Generalization: Supertypes and Subtypes
  • 2.2.2. Aggregation
  • 2.2.3. Ternary Relationships
  • 2.2.4. General n-ary Relationships
  • 2.2.5. Exclusion Constraint
  • 2.2.6. Referential Integrity
  • 2.3. Summary
  • 2.4. Literature Summary
  • Chapter 3. The Unified Modeling Language (UML)
  • 3.1. Class Diagrams
  • 3.1.1. Basic Class Diagram Notation
  • 3.1.2. Class Diagrams for Database Design
  • 3.1.3. Example from the Music Industry
  • 3.2. Activity Diagrams
  • 3.2.1. Activity Diagram Notation Description
  • 3.2.2. Activity Diagrams for Workflow
  • 3.3. Rules of Thumb for UML Usage
  • 3.4. Summary
  • 3.5. Literature Summary
  • Chapter 4. Requirements Analysis and Conceptual Data Modeling
  • 4.1. Introduction
  • 4.2. Requirements Analysis
  • 4.3. Conceptual Data Modeling
  • 4.3.1. Classify Entities and Attributes
  • 4.3.2. Identify the Generalization Hierarchies
  • 4.3.3. Define Relationships
  • 4.3.4. Example of Data Modeling: Company Personnel and Project Database
  • 4.4. View Integration
  • 4.4.1. Preintegration Analysis
  • 4.4.2. Comparison of Schemas
  • 4.4.3. Conformation of Schemas
  • 4.4.4. Merging and Restructuring of Schemas
  • 4.4.5. Example of View Integration
  • 4.5. Entity Clustering for ER Models
  • 4.5.1. Clustering Concepts
  • 4.5.2. Grouping Operations
  • 4.5.3. Clustering Technique
  • 4.6. Summary
  • 4.7. Literature Summary
  • Chapter 5. Transforming the Conceptual Data Model to SQL
  • 5.1. Transformation Rules and SQL Constructs
  • 5.1.1. Binary Relationships
  • 5.1.2. Binary Recursive Relationships
  • 5.1.3. Ternary and n-ary Relationships
  • 5.1.4. Generalization and Aggregation
  • 5.1.5. Multiple Relationships
  • 5.1.6. Weak Entities
  • 5.2. Transformation Steps
  • 5.2.1. Entity Transformation
  • 5.2.2. Many-to-Many Binary Relationship Transformation
  • 5.2.3. Ternary Relationship Transformation
  • 5.2.4. Example of ER-to-SQL Transformation
  • 5.3. Summary
  • 5.4. Literature Summary
  • Chapter 6. Normalization
  • 6.1. Fundamentals of Normalization
  • 6.1.1. First Normal Form
  • 6.1.2. Superkeys, Candidate Keys, and Primary Keys
  • 6.1.3. Second Normal Form
  • 6.1.4. Third Normal Form
  • 6.1.5. Boyce-Codd Normal Form
  • 6.2. The Design of Normalized Tables: A Simple Example
  • 6.3. Normalization of Candidate Tables Derived from ER Diagrams
  • 6.4. Determining the Minimum Set of 3NF Tables
  • 6.5. Fourth and Fifth Normal Forms
  • 6.5.1. Multivalued Dependencies
  • 6.5.2. Fourth Normal Form
  • 6.5.3. Decomposing Tables to 4NF
  • 6.5.4. Fifth Normal Form
  • 6.6. Summary
  • 6.7. Literature Summary
  • Chapter 7. An Example of Logical Database Design
  • 7.1. Requirements Specification
  • 7.1.1. Design Problems
  • 7.2. Logical Design
  • 7.3. Summary
  • Chapter 8. Business Intelligence
  • 8.1. Data Warehousing
  • 8.1.1. Overview of Data Warehousing
  • 8.1.2. Logical Design
  • 8.2. Online Analytical Processing (OLAP)
  • 8.2.1. The Exponential Explosion of Views
  • 8.2.2. Overview of OLAP
  • 8.2.3. View Size Estimation
  • 8.2.4. Selection of Materialized Views
  • 8.2.5. View Maintenance
  • 8.2.6. Query Optimization
  • 8.3. Data Mining
  • 8.3.1. Forecasting
  • 8.3.2. Text Mining
  • 8.4. Summary
  • 8.5. Literature Summary
  • Chapter 9. CASE Tools for Logical Database Design
  • 9.1. Introduction to the CASE Tools
  • 9.2. Key Capabilities to Watch For
  • 9.3. The Basics
  • 9.4. Generating a Database from a Design
  • 9.5. Database Support
  • 9.6. Collaborative Support
  • 9.7. Distributed Development
  • 9.8. Application Life Cycle Tooling Integration
  • 9.9. Design Compliance Checking
  • 9.10. Reporting
  • 9.11. Modeling a Data Warehouse
  • 9.12. Semi-Structured Data, XML
  • 9.13. Summary
  • 9.14. Literature Summary
  • Appendix. The Basics of SQL
  • Glossary
  • References
  • Exercises
  • Solutions to Selected Exercises
  • About the Authors
  • Index