{"product_id":"data-modeling-fundamentals-a-practical-guide-for-it-professionals-hardback-9780471790495","title":"Data Modeling Fundamentals; A Practical Guide for IT Professionals (Hardback) 9780471790495","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eData Modeling Fundamentals\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eA Practical Guide for IT Professionals\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003ePaulraj Ponniah (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471790495, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 7 August 2007\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e464 pages\u003cbr\u003e26 x 18.4 x 2.7 cm, 0.934 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eThe purpose of this book is to provide a practical approach for IT professionals to acquire the necessary knowledge and expertise in data modeling to function effectively. It begins with an overview of basic data modeling concepts, introduces the methods and techniques, provides a comprehensive case study to present the details of the data model components, covers the implementation of the data model with emphasis on quality components, and concludes with a presentation of a realistic approach to data modeling. It clearly describes how a generic data model is created to represent truly the enterprise information requirements.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I: INTRODUCTION TO DATA MODELING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1. Data Modeling: An Overview.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eData Model Defined.\u003c\/p\u003e \u003cp\u003eWhat is a Data Model?\u003c\/p\u003e \u003cp\u003eWhy Data Modeling?\u003c\/p\u003e \u003cp\u003eWho Performs Data Modeling?\u003c\/p\u003e \u003cp\u003eInformation Levels.\u003c\/p\u003e \u003cp\u003eClassification of Information Levels.\u003c\/p\u003e \u003cp\u003eData Models at Information Levels.\u003c\/p\u003e \u003cp\u003eConceptual Data Modeling.\u003c\/p\u003e \u003cp\u003eData Model Components.\u003c\/p\u003e \u003cp\u003eData Modeling Steps.\u003c\/p\u003e \u003cp\u003eData Model Quality.\u003c\/p\u003e \u003cp\u003eSignificance of Data Model Quality.\u003c\/p\u003e \u003cp\u003eData Model Characteristics.\u003c\/p\u003e \u003cp\u003eEnsuring Data Model Quality.\u003c\/p\u003e \u003cp\u003eData System Development.\u003c\/p\u003e \u003cp\u003eData System Development Life Cycle (DDLC).\u003c\/p\u003e \u003cp\u003eRoles and Responsibilities.\u003c\/p\u003e \u003cp\u003eModeling the Information Requirements.\u003c\/p\u003e \u003cp\u003eApplying Agile Modeling Principles.\u003c\/p\u003e \u003cp\u003eData Modeling Approaches and Trends.\u003c\/p\u003e \u003cp\u003eData Modeling Approaches.\u003c\/p\u003e \u003cp\u003eModeling for Data Warehouse.\u003c\/p\u003e \u003cp\u003eOther Modeling Trends.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. Methods, Techniques, and Symbols.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eData Modeling Approaches.\u003c\/p\u003e \u003cp\u003eSemantic Modeling.\u003c\/p\u003e \u003cp\u003eRelational Modeling.\u003c\/p\u003e \u003cp\u003eEntity-Relationship Modeling.\u003c\/p\u003e \u003cp\u003eBinary Modeling.\u003c\/p\u003e \u003cp\u003eMethods and Techniques.\u003c\/p\u003e \u003cp\u003ePeter Chen (E-R) Modeling.\u003c\/p\u003e \u003cp\u003eInformation Engineering.\u003c\/p\u003e \u003cp\u003eIDEF1X.\u003c\/p\u003e \u003cp\u003eRichard Barker’s.\u003c\/p\u003e \u003cp\u003eORM (Object Role Modeling).\u003c\/p\u003e \u003cp\u003eXML (eXtensible Markup Language).\u003c\/p\u003e \u003cp\u003eSummary and Comments.\u003c\/p\u003e \u003cp\u003eUnified Modeling Language (UML).\u003c\/p\u003e \u003cp\u003eData Modeling Using UML.\u003c\/p\u003e \u003cp\u003eUML in the Development Process.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II. DATA MODELING FUNDAMENTALS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. Anatomy of a Data Model.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eData Model Composition.\u003c\/p\u003e \u003cp\u003eModels at Different Levels.\u003c\/p\u003e \u003cp\u003eConceptual Model: Review Procedure.\u003c\/p\u003e \u003cp\u003eConceptual Model: Identifying Components.\u003c\/p\u003e \u003cp\u003eCase Study.\u003c\/p\u003e \u003cp\u003eDescription.\u003c\/p\u003e \u003cp\u003eE-R Model.\u003c\/p\u003e \u003cp\u003eUML Model.\u003c\/p\u003e \u003cp\u003eCreation of Models.\u003c\/p\u003e \u003cp\u003eUser Views.\u003c\/p\u003e \u003cp\u003eView Integration.\u003c\/p\u003e \u003cp\u003eEntity Types.\u003c\/p\u003e \u003cp\u003eSpecialization\/Generalization.\u003c\/p\u003e \u003cp\u003eRelationships.\u003c\/p\u003e \u003cp\u003eAttributes.\u003c\/p\u003e \u003cp\u003eIdentifiers.\u003c\/p\u003e \u003cp\u003eReview of the Model Diagram.\u003c\/p\u003e \u003cp\u003eLogical Model: Overview.\u003c\/p\u003e \u003cp\u003eModel Components.\u003c\/p\u003e \u003cp\u003eTransformation Steps.\u003c\/p\u003e \u003cp\u003eRelational Model.\u003c\/p\u003e \u003cp\u003ePhysical Model: Overview.\u003c\/p\u003e \u003cp\u003eModel Components.\u003c\/p\u003e \u003cp\u003eTransformation Steps.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4. Objects or Entities in Detail.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eEntity Types or Object Sets.\u003c\/p\u003e \u003cp\u003eComprehensive Definition.\u003c\/p\u003e \u003cp\u003eIdentifying Entity Types.\u003c\/p\u003e \u003cp\u003eHomonyms and Synonyms.\u003c\/p\u003e \u003cp\u003eCategory of Entity Types.\u003c\/p\u003e \u003cp\u003eExploring Dependencies.\u003c\/p\u003e \u003cp\u003eDependent or Weak Entity Types.\u003c\/p\u003e \u003cp\u003eClassifying Dependencies.\u003c\/p\u003e \u003cp\u003eRepresentation in the Model.\u003c\/p\u003e \u003cp\u003eGeneralization and Specialization.\u003c\/p\u003e \u003cp\u003eWhy Generalize or Specialize?\u003c\/p\u003e \u003cp\u003eSuper-types and Sub-types.\u003c\/p\u003e \u003cp\u003eGeneralization Hierarchy.\u003c\/p\u003e \u003cp\u003eInheritance of Attributes.\u003c\/p\u003e \u003cp\u003eInheritance of Relationships.\u003c\/p\u003e \u003cp\u003eConstraints.\u003c\/p\u003e \u003cp\u003eRules Summarized.\u003c\/p\u003e \u003cp\u003eSpecial Cases and Exceptions.\u003c\/p\u003e \u003cp\u003eRecursive Structures.\u003c\/p\u003e \u003cp\u003eConceptual and Physical.\u003c\/p\u003e \u003cp\u003eAssembly Structures.\u003c\/p\u003e \u003cp\u003eEntity Type Vs Attribute.\u003c\/p\u003e \u003cp\u003eEntity Type Vs Relationship.\u003c\/p\u003e \u003cp\u003eModeling Time Dimension.\u003c\/p\u003e \u003cp\u003eCategorization.\u003c\/p\u003e \u003cp\u003eEntity Validation Checklist.\u003c\/p\u003e \u003cp\u003eCompleteness.\u003c\/p\u003e \u003cp\u003eCorrectness.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. Attributes and Identifiers in Detail.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eAttributes.\u003c\/p\u003e \u003cp\u003eProperties or Characteristics.\u003c\/p\u003e \u003cp\u003eAttributes as Data.\u003c\/p\u003e \u003cp\u003eAttribute Values.\u003c\/p\u003e \u003cp\u003eNames and Descriptions.\u003c\/p\u003e \u003cp\u003eAttribute Domains.\u003c\/p\u003e \u003cp\u003eDefinition of a Domain.\u003c\/p\u003e \u003cp\u003eDomain Information.\u003c\/p\u003e \u003cp\u003eAttribute Values and Domains.\u003c\/p\u003e \u003cp\u003eSplit Domains.\u003c\/p\u003e \u003cp\u003eMisrepresented Domains.\u003c\/p\u003e \u003cp\u003eResolution of Mixed Domains.\u003c\/p\u003e \u003cp\u003eConstraints for Attributes.\u003c\/p\u003e \u003cp\u003eValue Set.\u003c\/p\u003e \u003cp\u003eRange.\u003c\/p\u003e \u003cp\u003eType.\u003c\/p\u003e \u003cp\u003eNull Values.\u003c\/p\u003e \u003cp\u003eTypes of Attributes.\u003c\/p\u003e \u003cp\u003eSingle-Valued and Multi-Valued Attributes.\u003c\/p\u003e \u003cp\u003eSimple and Composite Attributes.\u003c\/p\u003e \u003cp\u003eAttributes with Stored and Derived Values .\u003c\/p\u003e \u003cp\u003eOptional Attributes.\u003c\/p\u003e \u003cp\u003eIdentifiers or Keys.\u003c\/p\u003e \u003cp\u003eNeed for Identifiers.\u003c\/p\u003e \u003cp\u003eDefinitions of Keys.\u003c\/p\u003e \u003cp\u003eGuidelines for Identifiers.\u003c\/p\u003e \u003cp\u003eKey in Generalization Hierarchy.\u003c\/p\u003e \u003cp\u003eAttribute Validation Checklist.\u003c\/p\u003e \u003cp\u003eCompleteness.\u003c\/p\u003e \u003cp\u003eCorrectness.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Relationships in Detail.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eRelationships.\u003c\/p\u003e \u003cp\u003eAssociations.\u003c\/p\u003e \u003cp\u003eRelationship?Two-sided.\u003c\/p\u003e \u003cp\u003eRelationship Sets.\u003c\/p\u003e \u003cp\u003eDouble Relationships.\u003c\/p\u003e \u003cp\u003eRelationship Attributes.\u003c\/p\u003e \u003cp\u003eDegree of Relationships.\u003c\/p\u003e \u003cp\u003eUnary Relationship.\u003c\/p\u003e \u003cp\u003eBinary Relationship.\u003c\/p\u003e \u003cp\u003eTernary Relationship.\u003c\/p\u003e \u003cp\u003eQuaternary Relationship.\u003c\/p\u003e \u003cp\u003eStructural Constraints.\u003c\/p\u003e \u003cp\u003eCardinality Constraint.\u003c\/p\u003e \u003cp\u003eParticipation Constraint.\u003c\/p\u003e \u003cp\u003eDependencies.\u003c\/p\u003e \u003cp\u003eEntity Existence.\u003c\/p\u003e \u003cp\u003eRelationship Types.\u003c\/p\u003e \u003cp\u003eIdentifying Relationship .\u003c\/p\u003e \u003cp\u003eNon-identifying Relationship.\u003c\/p\u003e \u003cp\u003eMaximum and Minimum Cardinalities.\u003c\/p\u003e \u003cp\u003eMandatory Conditions - Both Ends.\u003c\/p\u003e \u003cp\u003eOptional Condition - One End.\u003c\/p\u003e \u003cp\u003eOptional Condition - Other End.\u003c\/p\u003e \u003cp\u003eOptional Conditions - Both Ends.\u003c\/p\u003e \u003cp\u003eSpecial Cases.\u003c\/p\u003e \u003cp\u003eGerund.\u003c\/p\u003e \u003cp\u003eAggregation.\u003c\/p\u003e \u003cp\u003eAccess Pathways.\u003c\/p\u003e \u003cp\u003eDesign Issues.\u003c\/p\u003e \u003cp\u003eRelationship Or Entity Type?\u003c\/p\u003e \u003cp\u003eTernary Relationship Or Aggregation?\u003c\/p\u003e \u003cp\u003eBinary Or N-ary Relationship?\u003c\/p\u003e \u003cp\u003eOne-to-One Relationships.\u003c\/p\u003e \u003cp\u003eOne-to-Many Relationships.\u003c\/p\u003e \u003cp\u003eCircular Structures.\u003c\/p\u003e \u003cp\u003eRedundant Relationships.\u003c\/p\u003e \u003cp\u003eMultiple Relationships.\u003c\/p\u003e \u003cp\u003eRelationship Validation Checklist.\u003c\/p\u003e \u003cp\u003eCompleteness.\u003c\/p\u003e \u003cp\u003eCorrectness.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III. DATA MODEL IMPLEMENTATION.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Data Modeling to Database Design.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eRelational Model: Fundamentals.\u003c\/p\u003e \u003cp\u003eBasic Concepts.\u003c\/p\u003e \u003cp\u003eStructure and Components.\u003c\/p\u003e \u003cp\u003eData Integrity Constraints.\u003c\/p\u003e \u003cp\u003eTransition to Database Design.\u003c\/p\u003e \u003cp\u003eDesign Approaches.\u003c\/p\u003e \u003cp\u003eConceptual to Relational Model.\u003c\/p\u003e \u003cp\u003eTraditional Method.\u003c\/p\u003e \u003cp\u003eEvaluation of Design Methods.\u003c\/p\u003e \u003cp\u003eModel Transformation Method.\u003c\/p\u003e \u003cp\u003eThe Approach.\u003c\/p\u003e \u003cp\u003eMapping of Components.\u003c\/p\u003e \u003cp\u003eEntity Types to Relations.\u003c\/p\u003e \u003cp\u003eAttributes to Columns.\u003c\/p\u003e \u003cp\u003eIdentifiers to Keys.\u003c\/p\u003e \u003cp\u003eTransformation of Relationships.\u003c\/p\u003e \u003cp\u003eTransformation Summary .\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. Data Normalization.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eInformal Design.\u003c\/p\u003e \u003cp\u003eForming Relations from Requirements.\u003c\/p\u003e \u003cp\u003ePotential Problems.\u003c\/p\u003e \u003cp\u003eUpdate Anomaly.\u003c\/p\u003e \u003cp\u003eDeletion Anomaly.\u003c\/p\u003e \u003cp\u003eAddition Anomaly.\u003c\/p\u003e \u003cp\u003eNormalization Methodology.\u003c\/p\u003e \u003cp\u003eStrengths of the Method.\u003c\/p\u003e \u003cp\u003eApplication of the Method.\u003c\/p\u003e \u003cp\u003eNormalization Steps.\u003c\/p\u003e \u003cp\u003eFundamental Normal Forms.\u003c\/p\u003e \u003cp\u003eFirst Normal Form.\u003c\/p\u003e \u003cp\u003eSecond Normal Form.\u003c\/p\u003e \u003cp\u003eThird Normal Form.\u003c\/p\u003e \u003cp\u003eBoyce-Codd Normal Form.\u003c\/p\u003e \u003cp\u003eHigher Normal Forms.\u003c\/p\u003e \u003cp\u003eFourth Normal Form.\u003c\/p\u003e \u003cp\u003eFifth Normal Form.\u003c\/p\u003e \u003cp\u003eDomain-Key Normal Form.\u003c\/p\u003e \u003cp\u003eNormalization Summary.\u003c\/p\u003e \u003cp\u003eReview of the Steps.\u003c\/p\u003e \u003cp\u003eNormalization as Verification.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. Modeling for Decision-Support Systems.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eDecision-Support Systems.\u003c\/p\u003e \u003cp\u003eNeed for Strategic Information.\u003c\/p\u003e \u003cp\u003eHistory of Decision-Support Systems.\u003c\/p\u003e \u003cp\u003eOperational Vs Informational Systems.\u003c\/p\u003e \u003cp\u003eSystem Types and Modeling Methods.\u003c\/p\u003e \u003cp\u003eData Warehouse.\u003c\/p\u003e \u003cp\u003eData Warehouse Defined.\u003c\/p\u003e \u003cp\u003eMajor Components.\u003c\/p\u003e \u003cp\u003eData Warehousing Applications.\u003c\/p\u003e \u003cp\u003eModeling: Special Requirements.\u003c\/p\u003e \u003cp\u003eDimensional Modeling.\u003c\/p\u003e \u003cp\u003eDimensional Modeling Basics.\u003c\/p\u003e \u003cp\u003eSTAR Schema.\u003c\/p\u003e \u003cp\u003eSnowflake Schema.\u003c\/p\u003e \u003cp\u003eFamilies of STARS.\u003c\/p\u003e \u003cp\u003eTransition to Logical Model.\u003c\/p\u003e \u003cp\u003eOLAP Systems.\u003c\/p\u003e \u003cp\u003eFeatures and Functions of OLAP.\u003c\/p\u003e \u003cp\u003eDimensional Analysis.\u003c\/p\u003e \u003cp\u003eHypercubes.\u003c\/p\u003e \u003cp\u003eOLAP Implementation Approaches.\u003c\/p\u003e \u003cp\u003eData Modeling for OLAP.\u003c\/p\u003e \u003cp\u003eData Mining Systems.\u003c\/p\u003e \u003cp\u003eBasic Concepts.\u003c\/p\u003e \u003cp\u003eData Mining Techniques.\u003c\/p\u003e \u003cp\u003eData Preparation and Modeling.\u003c\/p\u003e \u003cp\u003eData Preprocessing.\u003c\/p\u003e \u003cp\u003eData Modeling.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART IV. PRACTICAL APPROACH TO DATA MODELING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Ensuring Quality in the Data Model.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eSignificant of Quality.\u003c\/p\u003e \u003cp\u003eWhy Emphasize Quality?\u003c\/p\u003e \u003cp\u003eGood and Bad Models.\u003c\/p\u003e \u003cp\u003eApproach to Good Modeling.\u003c\/p\u003e \u003cp\u003eQuality of Definitions.\u003c\/p\u003e \u003cp\u003eImportance of Definitions.\u003c\/p\u003e \u003cp\u003eAspects of Quality Definitions.\u003c\/p\u003e \u003cp\u003eCorrectness.\u003c\/p\u003e \u003cp\u003eCompleteness.\u003c\/p\u003e \u003cp\u003eClearness.\u003c\/p\u003e \u003cp\u003eFormat.\u003c\/p\u003e \u003cp\u003eChecklists.\u003c\/p\u003e \u003cp\u003eHigh-Quality Data Model.\u003c\/p\u003e \u003cp\u003eMeaning of Data Model Quality.\u003c\/p\u003e \u003cp\u003eQuality Dimensions.\u003c\/p\u003e \u003cp\u003eWhat is a High-Quality Model?\u003c\/p\u003e \u003cp\u003eBenefits of High-Quality Models.\u003c\/p\u003e \u003cp\u003eQuality Assurance Process.\u003c\/p\u003e \u003cp\u003eAspects of Quality Assurance.\u003c\/p\u003e \u003cp\u003eStages of Quality Assurance Process.\u003c\/p\u003e \u003cp\u003eData Model Review.\u003c\/p\u003e \u003cp\u003eData Model Assessment.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Agile Data Modeling in Practice.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eThe Agile Movement.\u003c\/p\u003e \u003cp\u003eHow It Got Started.\u003c\/p\u003e \u003cp\u003ePrinciples of Agile Development.\u003c\/p\u003e \u003cp\u003ePhilosophies.\u003c\/p\u003e \u003cp\u003eGeneralizing Specialists.\u003c\/p\u003e \u003cp\u003eAgile Modeling.\u003c\/p\u003e \u003cp\u003eWhat is Agile Modeling?\u003c\/p\u003e \u003cp\u003eBasic Principles.\u003c\/p\u003e \u003cp\u003eAuxiliary Principles.\u003c\/p\u003e \u003cp\u003ePracticing Agile Modeling.\u003c\/p\u003e \u003cp\u003ePrimary Practices.\u003c\/p\u003e \u003cp\u003eAdditional Practices.\u003c\/p\u003e \u003cp\u003eRole of Agile DBA.\u003c\/p\u003e \u003cp\u003eAgile Documentation.\u003c\/p\u003e \u003cp\u003eRecognizing an Agile Model.\u003c\/p\u003e \u003cp\u003eFeasibility.\u003c\/p\u003e \u003cp\u003eEvolutionary Data Modeling.\u003c\/p\u003e \u003cp\u003eTraditional Approach.\u003c\/p\u003e \u003cp\u003eNeed for Flexibility.\u003c\/p\u003e \u003cp\u003eNature of Evolutionary Modeling.\u003c\/p\u003e \u003cp\u003eBenefits.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. Data Modeling: Practical Tips.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003eTips and Suggestions.\u003c\/p\u003e \u003cp\u003eNature of Tips.\u003c\/p\u003e \u003cp\u003eHow Specified.\u003c\/p\u003e \u003cp\u003eHow to Use Them.\u003c\/p\u003e \u003cp\u003eRequirements Definition.\u003c\/p\u003e \u003cp\u003eInterviews.\u003c\/p\u003e \u003cp\u003eGroup Sesssions.\u003c\/p\u003e \u003cp\u003eGeographically Dispersed Groups.\u003c\/p\u003e \u003cp\u003eDocumentation.\u003c\/p\u003e \u003cp\u003eChange Management.\u003c\/p\u003e \u003cp\u003eNotes for Modeling.\u003c\/p\u003e \u003cp\u003eStakeholder Participation.\u003c\/p\u003e \u003cp\u003eOrganizing Participation.\u003c\/p\u003e \u003cp\u003eUser Liaison.\u003c\/p\u003e \u003cp\u003eContinuous Interaction.\u003c\/p\u003e \u003cp\u003eMultiple Sites.\u003c\/p\u003e \u003cp\u003eIterative Modeling.\u003c\/p\u003e \u003cp\u003eEstablishing Cycles.\u003c\/p\u003e \u003cp\u003eDetermining Increments.\u003c\/p\u003e \u003cp\u003eRequirements--Model Interface.\u003c\/p\u003e \u003cp\u003eIntegration of Partial Models.\u003c\/p\u003e \u003cp\u003eSpecial Cases.\u003c\/p\u003e \u003cp\u003eLegal Entities.\u003c\/p\u003e \u003cp\u003eLocations and Places.\u003c\/p\u003e \u003cp\u003eTime Periods.\u003c\/p\u003e \u003cp\u003ePersons.\u003c\/p\u003e \u003cp\u003eBill-of-Materials.\u003c\/p\u003e \u003cp\u003eConceptual Model Layout.\u003c\/p\u003e \u003cp\u003eReadability and Usability.\u003c\/p\u003e \u003cp\u003eComponent Arrangement.\u003c\/p\u003e \u003cp\u003eAdding Texts.\u003c\/p\u003e \u003cp\u003eVisual Highlights.\u003c\/p\u003e \u003cp\u003eLogical Data Model.\u003c\/p\u003e \u003cp\u003eEnhancement Motivation.\u003c\/p\u003e \u003cp\u003eEasier DB Implementation.\u003c\/p\u003e \u003cp\u003ePerformance Improvement.\u003c\/p\u003e \u003cp\u003eStorage Management.\u003c\/p\u003e \u003cp\u003eEnhanced Representation.\u003c\/p\u003e \u003cp\u003eChapter Summary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eGlossary.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer networking \u0026amp; communications [\u003ca title=\"See our other books on Computer networking \u0026amp; communications\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20networking%20\u0026amp;%20communications%20%5BUT%5D%22\"\u003eUT\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Interscience","offers":[{"title":"Brand New","offer_id":52298057285912,"sku":"9780471790495","price":118.89,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780471790495.jpg?v=1781733454","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/data-modeling-fundamentals-a-practical-guide-for-it-professionals-hardback-9780471790495","provider":"Freshly Printed Books","version":"1.0","type":"link"}