Data Modeling Theory and Practice

Autor: 
Limba: 
english
Tip copertă: 
Moale
Număr de pagini: 
400
Graeme Simsion, author of several bestsellers including The Rosie Project, provides a detailed review of the extensive literature on data modeling and logical database design, referencing nearly 500 p ...Descriere completă
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ISBN9780977140015
AutorSimsion Graeme
EdituraTechnics Pubn Llc
Limbaenglish
Tip copertăPaperback
Anul publicării2007
Număr de pagini400

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Graeme Simsion, author of several bestsellers including The Rosie Project, provides a detailed review of the extensive literature on data modeling and logical database design, referencing nearly 500 publications, with a strong focus on their relevance to practice.

DATA MODELING THEORY AND PRACTICE is for practitioners and academics who have learned the conventions and rules of data modeling and are looking for a deeper understanding of the discipline. The coverage of theory includes a detailed review of the extensive literature on data modeling and logical database design, referencing nearly 500 publications, with a strong focus on their relevance to practice. The practice component incorporates the largest-ever study of data modeling practitioners, involving over 450 participants in interviews, surveys and data modeling tasks. The results challenge many longstanding held assumptions about data modeling and will be of interest to academics and practitioners alike.

Graeme Simsion brings to the book the practical perspective and intellectual clarity that have made his Data Modeling Essentials a classic in the field. He begins with a question about the nature of data modeling (design or description), and uses it to illuminate such issues as the definition of data modeling, its philosophical underpinnings, inputs and deliverables, the necessary behaviors and skills, the role of creativity, product diversity, quality measures, personal styles, and the differences between experts and novices.

Data Modeling Theory and Practice is essential reading for anyone involved in data modeling practice, research, or teaching.

 

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