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DATA MODELING MADE SIMPLE; A Practical Guide For Business & Information Technology Professionals
This book contains everthing 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!
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