book

Data Modeling, A Beginner's Guide

Name: Data Modeling, A Beginner's Guide
Author: Andy Oppel
ISBN: 9780071623995

by Andy Oppel

November 2009

Beginner

368 pages

9h 8m

English

McGraw-Hill

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Cover Page
Data Modeling A Beginner’s Guide
Copyright Page
Contents
Acknowledgments
Introduction
Part I Data Modeling Concepts
1 Introduction to Data Modeling
Data-Centric DesignAnatomy of a Data ModelLayers of Data AbstractionTypes of Data ModelsImportance of Data ModelingDocumentation of Business RulesVisualizationIllustration of AlternativesFoundation for Future ExpansionPromotion of Common and Standard StructuresProvisions for AutomationMeasures of a Good Data ModelEnforcement of Business RulesFlexible and AdaptableEasily UnderstoodBalanced PerspectivePromotion of Data ReusabilityData IntegrationHow Data Models Fit Into Application DevelopmentProcess-Oriented MethodologiesData-Oriented MethodologiesHybrid MethodologiesObject-Oriented MethodologiesPrototyping MethodologiesAgile MethodologiesData Modeling ParticipantsTry This 1-1: Refining a Conceptual ModelChapter 1 Self Test
2 Relational Model Components
Conceptual and Logical Model ComponentsEntitiesAttributesRelationshipsBusiness RulesPhysical Model ComponentsTablesColumns and Data TypesConstraintsIntegrity ConstraintsViewsTry This 2-1: Conceptual Model ModificationChapter 2 Self Test
3 Data and Process Modeling
Data Model Diagramming AlternativesERD FormatsRepresenting Supertypes and SubtypesGuidelines for Drawing ERDsProcess ModelsThe FlowchartThe Function Hierarchy DiagramThe Swim Lane DiagramThe Data Flow DiagramUnified Modeling Language (UML)UML Class DiagramsOther UML DiagramsRelating Entities and ProcessesTry This 3-1: Drawing a Conceptual Model with Nested SubtypesChapter 3 Self Test

4 Organizing Database Project Work
The Traditional Life CyclePlanningRequirements GatheringConceptual DesignLogical DesignPhysical DesignConstructionImplementation and RolloutOngoing SupportNontraditional Life CyclesPrototypingRapid Application DevelopmentThe Project TriangleTry This 4-1: Project Database Management TasksChapter 4 Self Test
Part II Data Modeling Details
5 Conceptual Data Modeling
The Conceptual Modeling ProcessPreparationSolution DesignWhat Differentiates Conceptual Modeling from Logical Modeling?Creating the ModelGeneric Models and PatternsRoles vs. SubtypesDealing with Hierarchies, Networks, and Linked ListsBottom Up vs. Top Down ModelingSubject AreasEvaluating the ModelWhat Makes a Good Conceptual Model?Try This 5-1: Conceptual Model for International AddressesChapter 5 Self Test
6 Logical Database Design Using Normalization
The Need for NormalizationInsert AnomalyDelete AnomalyUpdate AnomalyApplying the Normalization ProcessChoosing a Primary KeyFirst Normal Form: Eliminating Repeating DataSecond Normal Form: Eliminating Partial DependenciesThird Normal Form: Eliminating Transitive DependenciesDenormalizationPractice ProblemsTry This 6-1: UTLA Academic TrackingThe User ViewsTry This 6-2: Computer Books CompanyThe User ViewsChapter 6 Self Test
7 Beyond Third Normal Form
Advanced NormalizationBoyce-Codd Normal FormFourth Normal FormFifth Normal FormDomain-Key Normal Form (DKNF)Resolving Supertypes and SubtypesGeneralizing AttributesAlternatives for Reference DataCommon Code StructuresCrosswalk TablesLanguage Translation TablesTry This 7-1: Complex Logical Data ModelChapter 7 Self Test
8 Physical Database Design
The Physical Design ProcessDesigning TablesTry This 8-1: Drawing a Physical Data ModelImplementing Supertypes and SubtypesNaming ConventionsIntegrating Business Rules and Data IntegrityNOT NULL ConstraintsPrimary Key ConstraintsReferential (Foreign Key) ConstraintsUnique ConstraintsCheck ConstraintsData Types, Precision, and ScaleTriggersAdding Indexes for PerformanceDesigning ViewsTry This 8-2: Mapping a Logical Model to a Physical Database DesignChapter 8 Self Test
Part III Design Alternatives
9 Alternatives for Incorporating Business Rules
The Anatomy of a Business RuleThe Origin of Business RulesImplementing Business Rules in Data ModelsImplementing TermsImplementing FactsImplementing DerivationsLimitations on Implementing Business Rules in Data ModelsImplementing ConstraintsConstraints That Cannot Be Shown in Entity Relationship ModelsFunctional Classification of Business RulesDefinitional RulesData Validation RulesData Derivation RulesCardinality RulesReferential Integrity RulesProcess RulesTry This 9-1: Modeling Business RulesChapter 9 Self Test
10 Alternatives for Handling Temporal Data
Temporal Data StructuresWhen Does Time Matter?Adding History to Data StructuresProcessing Rules for HistoryHandling DeletionsCalendar Data StructuresBusiness Rules for Temporal DataTry This 10-1: Adding History to Data StructuresChapter 10 Self Test
11 Modeling for Analytical Databases
Data WarehousesOLTP Systems Compared with Data Warehouse SystemsData Warehouse ArchitectureData MartsModeling Analytical Data StructuresOLAP Database RequirementsData Warehouse ModelingData Mart ModelingLoading Data into Analytical DatabasesThe Extract ProcessThe Transform ProcessThe Load ProcessTry This 11-1: Design Star Schema Fact and Dimension TablesChapter 11 Self Test
12 Enterprise Data Modeling
Enterprise Data ManagementThe Case for Data ManagementAlternatives to Centralized Data ManagementThe Enterprise Data ModelWhat Is an Enterprise Data Model?The Anatomy of an Enterprise Data ModelBuilding an Enterprise Data ModelTry This 12-1: Enterprise Conceptual Model DevelopmentChapter 12 Self Test
Part IV Appendixes
A Answers to Self Tests
B Solutions to Try This Exercises
Try This 1-1: Refining a Conceptual ModelTry This 2-1: Conceptual Model ModificationTry This 3-1: Drawing a Conceptual Model with Nested SubtypesTry This 4-1: The Database Life CycleTry This 5-1: Conceptual Model for International AddressesTry This 6-1: UTLA Academic TrackingTry This 6-2: Computer Books CompanyTry This 7-1: Complex Logical Data ModelTry This 8-1: Drawing a Physical Data ModelTry This 8-2: Mapping a Logical Model to a Physical Database DesignTry This 9-1: Modeling Business RulesTry This 10-1: Adding History to Data StructuresTry This 11-1: Design Star Schema Fact and Dimension TablesTry This 12-1: Enterprise Conceptual Model Development
Index

Overview

Essential Skills--Made Easy!

Learn how to create data models that allow complex data to be analyzed, manipulated, extracted, and reported upon accurately. Data Modeling: A Beginner's Guide teaches you techniques for gathering business requirements and using them to produce conceptual, logical, and physical database designs. You'll get details on Unified Modeling Language (UML), normalization, incorporating business rules, handling temporal data, and analytical database design. The methods presented in this fast-paced tutorial are applicable to any database management system, regardless of vendor.

Designed for Easy Learning

Key Skills & Concepts--Chapter-opening lists of specific skills covered in the chapter
Ask the expert--Q&A sections filled with bonus information and helpful tips
Try This--Hands-on exercises that show you how to apply your skills
Notes--Extra information related to the topic being covered
Self Tests--Chapter-ending quizzes to test your knowledge

Andy Oppel has taught database technology for the University of California Extension for more than 25 years. He is the author of Databases Demystified, SQL Demystified, and Databases: A Beginner's Guide, and the co-author of SQL: A Beginner's Guide, Third Edition, and SQL: The Complete Reference, Third Edition.

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