Database modeling & design : logical design /

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Bibliographic Details
Author / Creator:Teorey, Toby J.
Edition:4th ed.
Imprint:Amsterdam : Elsevier ; Boston : Morgan Kaufmann Publishers, 2005.
Description:1 online resource (xviii, 275 pages) : illustrations.
Language:English
Series:Morgan Kaufmann series in data management systems
Morgan Kaufmann series in data management systems.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11152249
Hidden Bibliographic Details
Varying Form of Title:Database modeling and design
Other authors / contributors:Lightstone, Sam.
Nadeau, Tom.
ISBN:9780080470771
0080470777
9780126853520
0126853525
0126853525
Notes:Includes bibliographical references and index.
Print version record.
Summary:Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs? In the extensively revised fourth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rules that are applicable to any SQL-based system. But you'll also get plenty to help you grow from a new database designer to an experienced designer developing industrial-sized systems: 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--with examples throughout the book in both approaches; the details and examples of how to use data modeling concepts in logical database design, and the transformation of the conceptual model to the relational model and to SQL syntax; the fundamentals of database normalization through the fifth normal form; practical coverage of the major issues in business intelligence--data warehousing, OLAP for decision support systems, and data mining; examples for how to use the most popular CASE tools to handle complex data modeling problems; exercises that test understanding of all material, plus solutions for many exercises.
Other form:Print version: Teorey, Toby J. Database modeling & design. 4th ed. Amsterdam : Elsevier ; Boston : Morgan Kaufmann Publishers, 2005 0126853525 9780126853520
Table of Contents:
  • 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.