Serving as program and conference chair at the Working Conference on Reverse Engineering, Dr. Michael Blaha has authored six U.S. patents, four widely used books, and many papers while giving lectures throughout the world. Since 1994 Dr. Blaha has been a consultant and trainer in conceiving, architecting, modeling, designing, and tuning databases. He has worked with dozens of organizations throughout the world. He received his doctorate from Washington University in St. Louis and is an alumnus of GE Global Research in Schenectady, NY.
Best-selling author and database expert with more than 25 years of experience modeling application and enterprise data, Dr. Michael Blaha provides tried and tested data model patterns, to help readers avoid common modeling mistakes and unnecessary frustration on their way to building effective data models. Unlike the typical methodology book, Patterns of Data Modeling provides advanced techniques for those who have mastered the basics.
Recognizing that database representation sets the path for software, determines its flexibility, affects its quality, and influences whether it succeeds or fails, the text focuses on databases rather than programming. It is one of the first books to apply the popular patterns perspective to database systems and data models. It offers practical advice on the core aspects of applications and provides authoritative coverage of mathematical templates, antipatterns, archetypes, identity, canonical models, and relational database design.
Introduction. Mathematical Templates. Antipatterns. Archetypes. Identity. Canonical Models. Relational Database Design. Appendices.
Helping readers avoid common mistakes and build better models, this is one of the first books to apply the popular patterns perspective to database systems and the data models that are used to design state-of-the-art, efficient database systems. Best-selling author and database expert Dr. Michael Blaha provides detailed data model patterns as a basis for expertly building data models. Since most commercial software is built around a database, he focuses on databases rather than programming. He emphasizes how database representation sets the path for the software, determines its flexibility, affects its quality, and influences whether the software succeeds or fails.
Patterns of Data Modeling should be on the shelf of every database, software, and systems architect. The book captures decades of experience, presenting distilled knowledge in a concise and easy-to-understand format. The breadth of coverage is enormous, ranging from basic data structures through star schema, archetypes for representing commonly found concepts, and canonical models for tough problems.
—Paul C. Brown, Principal Software Architect, TIBCO Software Inc.
Mike Blaha has written a clear book with precise definitions and excellent examples. All examples are presented in a graphical form that is easy to read and understand. Blaha assumes the reader has a basic understanding of data modeling, but gives his examples in such a way that if the reader needs some review, it is built in.
—Toby Teorey, author of Database Modeling and Design, Fourth Edition
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Offers tried and tested data model patterns, to help readers avoid common modeling mistakes in building effective data models. This book provides advanced techniques for those who have mastered the basics. It focuses on databases rather than programming. It applies the patterns perspective to database systems and data models.
Über den Autor
Serving as program and conference chair at the Working Conference on Reverse Engineering, Dr. Michael Blaha has authored six U.S. patents, four widely used books, and many papers while giving lectures throughout the world. Since 1994 Dr. Blaha has been a consultant and trainer in conceiving, architecting, modeling, designing, and tuning databases. He has worked with dozens of organizations throughout the world. He received his doctorate from Washington University in St. Louis and is an alumnus of GE Global Research in Schenectady, NY.
Inhaltsverzeichnis
Introduction What Is a Model? Modeling Notation What Is a Pattern? Why are Patterns Important? Drawbacks of Patterns Pattern vs. Seed Model Aspects of Pattern Technology MATHEMATICAL TEMPLATES Tree Template Hardcoded Tree Template Simple Tree Template Structured Tree Template Overlapping Trees Template Tree Changing Over Time Template Degenerate Node and Edge Template Directed Graph Template Simple Directed Graph Template Structured Directed Graph Template Node and Edge Directed Graph Template Connection Directed Graph Template Simple DG Changing Over Time Template Node and Edge DG Changing Over Time Template Undirected Graph Template Node and Edge Undirected Graph Template Connection Undirected Graph Template Undirected Graph Changing Over Time Template Item Deillegalscription Template Item Deillegalscription Template Homomorphism Template Star Schema Template Star Schema Template Summary of Templates ANTIPATTERNS Universal Antipatterns Symmetric Relationship Antipattern Dead Elements Antipattern Disguised Fields Antipattern Artificial Hardcoded Levels Antipattern Excessive Generalization Antipattern Disconnected Entity Types Antipattern Modeling Errors Antipattern Multiple Inheritance Antipattern Paradigm Degradation Antipattern Non-Data-Warehouse Antipatterns Derived Data Antipattern Parallel Attributes Antipattern Parallel Relationships Antipattern Combined Entity Types Antipattern ARCHETYPES Archetypes Account Actor Address Asset Contract Course Customer Document Event Flight Item Location Opportunity Part Payment Position Product Role Transaction Vendor IDENTITY Identity Intrinsic Identity Names Surrogate Identity Structured Fields Master Applications Merging Data CANONICAL MODELS Language Translation Alternative Architectures Attribute Translation in Place Phrase-to-Phrase Translation Language-Neutral Translation Softcoded Values UML Model IDEF1X Model Architecture Softcoding Variations Generic Diagrams Generic Diagram Examples Diagram Subject Area Model Subject Area Model-Diagram Binding Subject Area Diagram Type Subject Area Diagram Example, Revisited State Diagrams State Diagrams Scenarios RELATIONAL DATABASE DESIGN Relational Database Design Mapping: Entity Types Mapping: Non-Qualified Relationships Mapping Qualified Relationships Mapping: Generalizations Design Identity Referential Integrity Miscellaneous Database Constraints Indexes Generating SQL Code APPENDICES Explanation of the UML Notation Entity Type Relationships Generalization Explanation of the IDEF1X Notation Entity Type Relationships Generalization Glossary Index All chapters conclude with a chapter summary; most include bibliographic notes & references
Klappentext
Offers tried and tested data model patterns, to help readers avoid common modeling mistakes in building effective data models. This book provides advanced techniques for those who have mastered the basics. It focuses on databases rather than programming. It applies the patterns perspective to database systems and data models.
