Data Modeling (Contemporary Issues in Information Systems) Review

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(More customer reviews)I have introduced a good variety of developers and analysts to this little book with a positive reaction on all occasions. It makes very few assumptions and moves rapidly from the introductory level to advanced practicality. The author has a style which is commendably concise and precise, relaxed but not wordy, illustrating with copious diagrams. His enthusiasm and professional attitude are obvious, his experience coming from extensive teaching and consulting in the USA and China. He promotes data modeling and database design for systems of any size by entity relationship analysis and diagramming and speaks as a generalist, not tied to any specific database technology.
Chapter 1: the difference between conceptual, logical, and physical database design. Good for those who need to be released from inveterately thinking at the physical level.
Chapter 2: the Entity Relationship Diagram (ERD), entity attributes, cardinality, recursive relationships, optional/mandatory bounds, and a fascination little section on Quillan's semantic data model for artificial intelligence (AI) knowledge modelling.
Chapter 3: how to convert ERD's to relational tables, and performance v. flexibility.
Chapter 4: worked examples - a range of simple starter data models. Includes Human Resources dept., tech support, ticket reservation systems, a charity, industrial production operations manage systems, and activity-based costing.
Chapter 5: strategic database planning across the organisation to avoid duplication of effort.
Chapter 6: Object-oriented data modeling (unfortunately predating UML, time for a second edition Lawrence!).
The appendix covers normalization of a relational data model beautifully, including create/update/delete anomalies, functional dependency between attributes, and Normal Form (first normal form, second normal form, third normal form, and domain key normal form (DKNF)). There is an useful reference bibliography and index.
Excellent value, highly recommended.

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Focusing on fundamental data modeling concepts, this text prepares readers to design, build, and implement systems of higher organizational value.

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