Data Modeling Made Simple
Subtitle: A Practical Guide for Business & Information Technology Professionals
Publisher: Technics Publications, LLC; Technics Publications
Published: October 17, 2005
Language: eng
Format: Paperback
Number of pages: 144
ISBN-13: 9780977140008
Subjects: Business & Management; Computing and Information Technology; Data analysis: general; Database Engineering; Computers; Computers - Data Base Management; Computer Books: General; Data Modeling & Design; Computers / General; Database Management - General
First sentence: I gave the steering wheel a heavy tap with my hands as I realized that, once again, I was completely lost.
Table of contents: title: Acknowledgements
pagenum: i; title: Foreword
pagenum: iii; title: Introduction
pagenum: v; label: Chapter 1
title: What Is a Data Model?
pagenum: 7; label: Chapter 2
title: What Is So Special About Data Models?
pagenum: 11; title: Communication
pagenum: 11; title: Formalization
pagenum: 13; title: Scope
pagenum: 14; title: Focus
pagenum: 16; label: Chapter 3
title: What Are Entities?
pagenum: 19; title: Independent
pagenum: 20; title: Dependent
pagenum: 21; label: Chapter 4
title: What Are Data Elements?
pagenum: 27; title: Domain
pagenum: 28; title: Keys
pagenum: 29; label: Chapter 5
title: What Are Relationships?
pagenum: 33; title: Cardinality
pagenum: 35; title: Recursion
pagenum: 37; title: Identifying and Non-Identifying Relationships
pagenum: 40; title: Relationship Labels
pagenum: 41; label: Chapter 6
title: What Makes a Definition Great?
pagenum: 43; title: Clarity
pagenum: 44; title: Completeness
pagenum: 44; title: Accuracy
pagenum: 45; label: Chapter 7
title: What Is the Subject Area Model?
pagenum: 47; title: Business Subject Area Model (BSAM)
pagenum: 48; title: Application Subject Area Model (ASAM)
pagenum: 51; title: Comparison Subject Area Model (CSAM)
pagenum: 53; label: Chapter 8
title: What Is the Logical Data Model?
pagenum: 55; title: Normalization
pagenum: 55; title: Starting With Chaos
pagenum: 57; title: First Normal Form (1NF)
pagenum: 60; title: Second Normal Form (2NF)
pagenum: 68; title: Third Normal Form (3NF)
pagenum: 71; title: Abstraction
pagenum: 74; label: Chapter 9
title: What Is the Physical Data Model?
pagenum: 81; title: Denormalization
pagenum: 81; title: Surrogate Keys
pagenum: 93; title: Indexing
pagenum: 95; title: Partitioning
pagenum: 96; title: Views
pagenum: 97; title: Dimensionality
pagenum: 99; label: Chapter 10
title: What Is the Best Approach to Build the Models?
pagenum: 105; title: Purpose + Audience = Deliverables
pagenum: 105; title: Deliverables + Resources + Time = Approach
pagenum: 107; label: Chapter 11
title: How Do I Validate a Data Model?
pagenum: 111; label: 1
title: How Well Does the Model Capture the Requirements?
pagenum: 113; label: 2
title: How Complete Is the Model?
pagenum: 116; label: 3
title: How Structurally Sound Is the Model?
pagenum: 117; label: 4
title: How Well Does the Model Leverage Generic Structures?
pagenum: 119; label: 5
title: How Well Does the Model Follow Naming Standards?
pagenum: 120; label: 6
title: How Well Has the Model Been Arranged for Readability?
pagenum: 121; label: 7
title: How Good Are the Definitions?
pagenum: 122; label: 8
title: How Well Has the Real World Context Been Incorporated?
pagenum: 123; label: 9
title: How Consistent Is the Model With the Enterprise?
pagenum: 124; label: 10
title: How Well Does the Metadata Match the Data?
pagenum: 125; label: Chapter 12
title: Top 3 Most Frequently Asked Questions
pagenum: 127; title: How Do I Keep My Modeling Skills Sharp?
pagenum: 127; title: What Is the Best Data Modeling Tool?
pagenum: 128; title: What Is the Future Role of the Data Modeler?
pagenum: 128; title: Suggested Reading
pagenum: 131; title: Books
pagenum: 131; title: Web Sites
pagenum: 131