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| Categorie: | Algemeen - Boeken | Van: | Technics Publications |
| Meer informatie: | www.technicspub.com ... | Info-file: | big_front_DataModeli... |
| Auteur(s): | Steve Hoberman | Bladzijden: | 134 |
| Publicatie-jaar: | 2005 | ||
This book contains everything about modeling you need to know but were too afraid to ask, such as:- What are the traditional and nontraditional uses of a data model? - How do subject area, logical, and physical data models differ? - When do I build a BSAM, ASAM, or CSAM?- What is the easiest way to apply normalization?- Where can I best leverage abstraction?- How do I decide whether to use denormalization or dimensionality? - What are primary, foreign, alternate, virtual, and surrogate » Lees meer... |  |
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This book contains everything about modeling you need to know but were too afraid to ask, such as:- What are the traditional and nontraditional uses of a data model? - How do subject area, logical, and physical data models differ? - When do I build a BSAM, ASAM, or CSAM?- What is the easiest way to apply normalization?- Where can I best leverage abstraction?- How do I decide whether to use denormalization or dimensionality? - What are primary, foreign, alternate, virtual, and surrogate keys?- What is the best approach to building the models?- How can I use the Scorecard system to validate a data model?- Plus over 30 exercises to reinforce concepts and sharpen your skills.For those who are not data modelers but need to work with them, this book is an excellent primer. For those who model data occasionally but not routinely, it is an invaluable quick reference. And for those of us who are experienced (and incorrigible) data modelers, Data Modeling Made Simple is a terrific reminder that we really can keep it simple.