Database modeling & design : logical design

Database modeling & design logical design

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Detalles Bibliográficos
Autor principal: Teorey, Toby J. (-)
Otros Autores: Lightstone, Sam, Nadeau, Tom
Formato: Libro electrónico
Idioma:Inglés
Publicado: Amsterdam : Boston : Elsevier ; Morgan Kaufmann Publishers 2005.
Edición:4th ed
Colección:EBSCO Academic eBook Collection Complete.
Morgan Kaufmann series in data management systems.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b3170640x*spi
Tabla de Contenidos:
  • Cover
  • Contents
  • Preface
  • Organization
  • Typographical Conventions
  • Acknowledgments
  • Solutions Manual
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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 Normalizati.

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