Database modeling & design logical design
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 mo...
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| Otros Autores: | , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Amsterdam : Boston :
Elsevier ; Morgan Kaufmann Publishers
2006.
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| Edición: | 4th ed |
| Colección: | The Morgan Kaufmann Series in Data Management Systems
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627311606719 |
Tabla de Contenidos:
- front cover; copyright; table of contents; front matter; Preface; Organization; Typographical Conventions; Acknowledgments; Solutions Manual; body; 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 Notations2.2 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 Usage3.4 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 Models4.5.1 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 Transformation5.3 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 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
