[payto](seller)yangyang9189@126.com(/seller)(subject)Data Mining essentials 数据挖掘的本质(/subject)(body)<p>Data Mining essentials （Third Edition）</p><p>Graeme C. Simsion and Graham C. Witt</p><p>Chapter 1<br/>What Is Data Modeling? 3<br/>1.1 Introduction 3<br/>1.2 A Data-Centered Perspective 3<br/>1.3 A Simple Example 4<br/>1.4 Design, Choice, and Creativity 6<br/>1.5 Why Is the Data Model Important? 8<br/>1.5.1 Leverage 8<br/>1.5.2 Conciseness 9<br/>1.5.3 Data Quality 10<br/>1.5.4 Summary 10<br/>1.6 What Makes a Good Data Model? 10<br/>1.6.1 Completeness 10<br/>1.6.2 NonRedundancy 11<br/>1.6.3 Enforcement of Business Rules 11<br/>1.6.4 Data Reusability 11<br/>1.6.5 Stability and Flexibility 12<br/>1.6.6 Elegance 13<br/>1.6.7 Communication 14<br/>1.6.8 Integration 14<br/>1.6.9 Conflicting Objectives 15<br/>1.7 Performance 15<br/>1.8 Database Design Stages and Deliverables 16<br/>1.8.1 Conceptual, Logical, and Physical Data Models 16<br/>1.8.2 The Three-Schema Architecture and Terminology 17</p><p>1.9 Where Do Data Models Fit In? 20<br/>1.9.1 Process-Driven Approaches 20<br/>1.9.2 Data-Driven Approaches 20<br/>1.9.3 Parallel (Blended) Approaches 22<br/>1.9.4 Object-Oriented Approaches 22<br/>1.9.5 Prototyping Approaches 23<br/>1.9.6 Agile Methods 23<br/>1.10 Who Should Be Involved in Data Modeling? 23<br/>1.11 Is Data Modeling Still Relevant? 24<br/>1.11.1 Costs and Benefits of Data Modeling 25<br/>1.11.2 Data Modeling and Packaged Software 26<br/>1.11.3 Data Integration 27<br/>1.11.4 Data Warehouses 27<br/>1.11.5 Personal Computing and User-Developed Systems 28<br/>1.11.6 Data Modeling and XML 28<br/>1.11.7 Summary 28<br/>1.12 Alternative Approaches to Data Modeling 29<br/>1.13 Terminology 30<br/>1.14 Where to from Here?—An Overview of Part I 31<br/>1.15 Summary 32<br/>Chapter 2<br/>Basics of Sound Structure 33<br/>2.1 Introduction 33<br/>2.2 An Informal Example of Normalization 34<br/>2.3 Relational Notation 36<br/>2.4 A More Complex Example 37<br/>2.5 Determining Columns 40<br/>2.5.1 One Fact per Column 40<br/>2.5.2 Hidden Data 41<br/>2.5.3 Derivable Data 41<br/>2.5.4 Determining the Primary Key 41<br/>2.6 Repeating Groups and First Normal Form 43<br/>2.6.1 Limit on Maximum Number of Occurrences 43<br/>2.6.2 Data Reusability and Program Complexity 43<br/>2.6.3 Recognizing Repeating Groups 44<br/>2.6.4 Removing Repeating Groups 45</p><p>2.6.5 Determining the Primary Key of the New Table 46<br/>2.6.6 First Normal Form 47<br/>2.7 Second and Third Normal Forms 47<br/>2.7.1 Problems with Tables in First Normal Form 47<br/>2.7.2 Eliminating Redundancy 48<br/>2.7.3 Determinants 48<br/>2.7.4 Third Normal Form 51<br/>2.8 Definitions and a Few Refinements 53<br/>2.8.1 Determinants and Functional Dependency 53<br/>2.8.2 Primary Keys 54<br/>2.8.3 Candidate Keys 54<br/>2.8.4 A More Formal Definition of Third Normal Form 55<br/>2.8.5 Foreign Keys 55<br/>2.8.6 Referential Integrity 56<br/>2.8.7 Update Anomalies 57<br/>2.8.8 Denormalization and Unnormalization 58<br/>2.8.9 Column and Table Names 59<br/>2.9 Choice, Creativity, and Normalization 60<br/>2.10 Terminology 62<br/>2.11 Summary 63<br/>Chapter 3<br/>The Entity-Relationship Approach 65<br/>3.1 Introduction 65<br/>3.2 A Diagrammatic Representation 65<br/>3.2.1 The Basic Symbols: Boxes and Arrows 66<br/>3.2.2 Diagrammatic Representation of Foreign Keys 67<br/>3.2.3 Interpreting the Diagram 68<br/>3.2.4 Optionality 69<br/>3.2.5 Verifying the Model 70<br/>3.2.6 Redundant Arrows 71<br/>3.3 The Top-Down Approach: Entity-Relationship<br/>Modeling 72<br/>3.3.1 Developing the Diagram Top Down 74<br/>3.3.2 Terminology 75<br/>3.4 Entity Classes 76<br/>3.4.1 Entity Diagramming Convention 77<br/>3.4.2 Entity Class Naming 78<br/>3.4.3 Entity Class Definitions 80</p><p>3.5 Relationships 82<br/>3.5.1 Relationship Diagramming Conventions 82<br/>3.5.2 Many-to-Many Relationships 87<br/>3.5.3 One-to-One Relationships 92<br/>3.5.4 Self-Referencing Relationships 93<br/>3.5.5 Relationships Involving Three or More Entity Classes 96<br/>3.5.6 Transferability 98<br/>3.5.7 Dependent and Independent Entity Classes 102<br/>3.5.8 Relationship Names 103<br/>3.6 Attributes 104<br/>3.6.1 Attribute Identification and Definition 104<br/>3.6.2 Primary Keys and the Conceptual Model 105<br/>3.7 Myths and Folklore 105<br/>3.7.1 Entity Classes without Relationships 106<br/>3.7.2 Allowed Combinations of Cardinality and Optionality 106<br/>3.8 Creativity and E-R Modeling 106<br/>3.9 Summary 109<br/>Chapter 4<br/>Subtypes and Supertypes 111<br/>4.1 Introduction 111<br/>4.2 Different Levels of Generalization 111<br/>4.3 Rules versus Stability 113<br/>4.4 Using Subtypes and Supertypes 115<br/>4.5 Subtypes and Supertypes as Entity Classes 116<br/>4.5.1 Naming Subtypes 117<br/>4.6 Diagramming Conventions 117<br/>4.6.1 Boxes in Boxes 117<br/>4.6.2 UML Conventions 118<br/>4.6.3 Using Tools That Do Not Support Subtyping 119<br/>4.7 Definitions 119<br/>4.8 Attributes of Supertypes and Subtypes 119<br/>4.9 Nonoverlapping and Exhaustive 120</p><p>4.10 Overlapping Subtypes and Roles 123<br/>4.10.1 Ignoring Real-World Overlaps 123<br/>4.10.2 Modeling Only the Supertype 124<br/>4.10.3 Modeling the Roles as Participation in Relationships 124<br/>4.10.4 Using Role Entity Classes and One-to-One Relationships 125<br/>4.10.5 Multiple Partitions 126<br/>4.11 Hierarchy of Subtypes 127<br/>4.12 Benefits of Using Subtypes and Supertypes 128<br/>4.12.1 Creativity 129<br/>4.12.2 Presentation: Level of Detail 129<br/>4.12.3 Communication 130<br/>4.12.4 Input to the Design of Views 132<br/>4.12.5 Classifying Common Patterns 132<br/>4.12.6 Divide and Conquer 133<br/>4.13 When Do We Stop Supertyping and Subtyping? 134<br/>4.13.1 Differences in Identifiers 134<br/>4.13.2 Different Attribute Groups 135<br/>4.13.3 Different Relationships 135<br/>4.13.4 Different Processes 136<br/>4.13.5 Migration from One Subtype to Another 136<br/>4.13.6 Communication 136<br/>4.13.7 Capturing Meaning and Rules 137<br/>4.13.8 Summary 137<br/>4.14 Generalization of Relationships 138<br/>4.14.1 Generalizing Several One-to-Many Relationships to a Single Many-to-<br/>Many Relationship 138<br/>4.14.2 Generalizing Several One-to-Many Relationships<br/>to a Single One-to-Many Relationship 139<br/>4.14.3 Generalizing One-to-Many and Many-to-Many Relationships 141<br/>4.15 Theoretical Background 142<br/>4.16 Summary 143<br/>Chapter 5<br/>Attributes and Columns 145<br/>5.1 Introduction 145<br/>5.2 Attribute Definition 146</p><p>5.3 Attribute Disaggregation: One Fact per Attribute 147<br/>5.3.1 Simple Aggregation 148<br/>5.3.2 Conflated Codes 150<br/>5.3.3 Meaningful Ranges 151<br/>5.3.4 Inappropriate Generalization 151<br/>5.4 Types of Attributes 152<br/>5.4.1 DBMS Datatypes 152<br/>5.4.2 The Attribute Taxonomy in Detail 154<br/>5.4.3 Attribute Domains 158<br/>5.4.4 Column Datatype and Length Requirements 162<br/>5.4.5 Conversion Between External and Internal Representations 166<br/>5.5 Attribute Names 166<br/>5.5.1 Objectives of Standardizing Attribute Names 166<br/>5.5.2 Some Guidelines for Attribute Naming 168<br/>5.6 Attribute Generalization 171<br/>5.6.1 Options and Trade-Offs 171<br/>5.6.2 Attribute Generalization Resulting from Entity Generalization 172<br/>5.6.3 Attribute Generalization within Entity Classes 173<br/>5.6.4 “First Among Equals” 177<br/>5.6.5 Limits to Attribute Generalization 178<br/>5.7 Summary 180<br/>Chapter 6<br/>Primary Keys and Identity 183<br/>6.1 Basic Requirements and Trade-Offs 183<br/>6.2 Basic Technical Criteria 185<br/>6.2.1 Applicability 185<br/>6.2.2 Uniqueness 186<br/>6.2.3 Minimality 188<br/>6.2.4 Stability 189<br/>6.3 Surrogate Keys 191<br/>6.3.1 Performance and Programming Issues 191<br/>6.3.2 Matching Real-World Identifiers 191<br/>6.3.3 Should Surrogate Keys Be Visible? 192<br/>6.3.4 Subtypes and Surrogate Keys 193<br/>6.4 Structured Keys 194<br/>6.4.1 When to Use Structured Keys 196<br/>6.4.2 Programming and Structured Keys 197<br/>6.4.3 Performance Issues with Structured Keys 198<br/>6.4.4 Running Out of Numbers 199</p><p>6.5 Multiple Candidate Keys 201<br/>6.5.1 Choosing a Primary Key 201<br/>6.5.2 Normalization Issues 201<br/>6.6 Guidelines for Choosing Keys 202<br/>6.6.1 Tables Implementing Independent Entity Classes 202<br/>6.6.2 Tables Implementing Dependent Entity Classes and Many-to-Many<br/>Relationships 203<br/>6.7 Partially-Null Keys 204<br/>6.8 Summary 206<br/>Chapter 7<br/>Extensions and Alternatives 207<br/>7.1 Introduction 207<br/>7.2 Extensions to the Basic E-R Approach 209<br/>7.2.1 Introduction 209<br/>7.2.2 Advanced Attribute Concepts 210<br/>7.3 The Chen E-R Approach 216<br/>7.3.1 The Basic Conventions 216<br/>7.3.2 Relationships with Attributes 217<br/>7.3.3 Relationships Involving Three or More Entity Classes 217<br/>7.3.4 Roles 218<br/>7.3.5 The Weak Entity Concept 219<br/>7.3.6 Chen Conventions in Practice 220<br/>7.4 Using UML Object Class Diagrams 220<br/>7.4.1 A Conceptual Data Model in UML 221<br/>7.4.2 Advantages of UML 222<br/>7.5 Object Role Modeling 227<br/>7.6 Summary 228<br/>Part II<br/>Putting It Together 229<br/>Chapter 8<br/>Organizing the Data Modeling Task 231<br/>8.1 Data Modeling in the Real World 231<br/>8.2 Key Issues in Project Organization 233<br/>8.2.1 Recognition of Data Modeling 233<br/>8.2.2 Clear Use of the Data Model 234</p><p>8.2.3 Access to Users and Other Business Stakeholders 234<br/>8.2.4 Conceptual, Logical, and Physical Models 235<br/>8.2.5 Cross-Checking with the Process Model 236<br/>8.2.6 Appropriate Tools 237<br/>8.3 Roles and Responsibilities 238<br/>8.4 Partitioning Large Projects 240<br/>8.5 Maintaining the Model 242<br/>8.5.1 Examples of Complex Changes 242<br/>8.5.2 Managing Change in the Modeling Process 247<br/>8.6 Packaging It Up 248<br/>8.7 Summary 249<br/>Chapter 9<br/>The Business Requirements 251<br/>9.1 Purpose of the Requirements Phase 251<br/>9.2 The Business Case 253<br/>9.3 Interviews and Workshops 254<br/>9.3.1 Should You Model in Interviews and Workshops? 255<br/>9.3.2 Interviews with Senior Managers 256<br/>9.3.3 Interviews with Subject Matter Experts 257<br/>9.3.4 Facilitated Workshops 257<br/>9.4 Riding the Trucks 258<br/>9.5 Existing Systems and Reverse<br/>Engineering 259<br/>9.6 Process Models 261<br/>9.7 Object Class Hierarchies 261<br/>9.7.1 Classifying Object Classes 263<br/>9.7.2 A Typical Set of Top-Level Object Classes 265<br/>9.7.3 Developing an Object Class Hierarchy 267<br/>9.7.4 Potential Issues 270<br/>9.7.5 Advantages of the Object Class Hierarchy Technique 270<br/>9.8 Summary 270</p><p>Chapter 10.<br/>Conceptual Data Modeling 273<br/>10.1 Designing Real Models 273<br/>10.2 Learning from Designers in Other Disciplines 275<br/>10.3 Starting the Modeling 276<br/>10.4 Patterns and Generic Models 277<br/>10.4.1 Using Patterns 277<br/>10.4.2 Using a Generic Model 278<br/>10.4.3 Adapting Generic Models from Other Applications 279<br/>10.4.4 Developing a Generic Model 282<br/>10.4.5 When There Is Not a Generic Model 284<br/>10.5 Bottom-Up Modeling 285<br/>10.6 Top-Down Modeling 288<br/>10.7 When the Problem Is Too Complex 288<br/>10.8 Hierarchies, Networks, and Chains 290<br/>10.8.1 Hierarchies 291<br/>10.8.2 Networks (Many-to-Many Relationships) 293<br/>10.8.3 Chains (One-to-One Relationships) 295<br/>10.9 One-to-One Relationships 295<br/>10.9.1 Distinct Real-World Concepts 296<br/>10.9.2 Separating Attribute Groups 297<br/>10.9.3 Transferable One-to-One Relationships 298<br/>10.9.4 Self-Referencing One-to-One Relationships 299<br/>10.9.5 Support for Creativity 299<br/>10.10 Developing Entity Class Definitions 300<br/>10.11 Handling Exceptions 301<br/>10.12 The Right Attitude 302<br/>10.12.1 Being Aware 303<br/>10.12.2 Being Creative 303<br/>10.12.3 Analyzing or Designing 303<br/>10.12.4. Being Brave 304<br/>10.12.5 Being Understanding and Understood 304<br/>10.13 Evaluating the Model 305<br/>10.14 Direct Review of Data Model Diagrams 306</p><p>10.15 Comparison with the Process Model 308<br/>10.16 Testing the Model with Sample Data 308<br/>10.17 Prototypes 309<br/>10.18 The Assertions Approach 309<br/>10.18.1 Naming Conventions 310<br/>10.18.2 Rules for Generating Assertions 311<br/>10.19 Summary 319<br/>Chapter 11<br/>Logical Database Design 321<br/>11.1 Introduction 321<br/>11.2 Overview of the Transformations<br/>Required 322<br/>11.3 Table Specification 325<br/>11.3.1 The Standard Transformation 325<br/>11.3.2 Exclusion of Entity Classes from the Database 325<br/>11.3.3 Classification Entity Classes 325<br/>11.3.4 Many-to-Many Relationship Implementation 326<br/>11.3.5 Relationships Involving More Than Two Entity Classes 328<br/>11.3.6 Supertype/Subtype Implementation 328<br/>11.4 Basic Column Definition 334<br/>11.4.1 Attribute Implementation: The Standard Transformation 334<br/>11.4.2 Category Attribute Implementation 335<br/>11.4.3 Derivable Attributes 336<br/>11.4.4 Attributes of Relationships 336<br/>11.4.5 Complex Attributes 337<br/>11.4.6 Multivalued Attribute Implementation 337<br/>11.4.7 Additional Columns 339<br/>11.4.8 Column Datatypes 340<br/>11.4.9 Column Nullability 340<br/>11.5 Primary Key Specification 341<br/>11.6 Foreign Key Specification 342<br/>11.6.1 One-to-Many Relationship Implementation 343<br/>11.6.2 One-to-One Relationship Implementation 346<br/>11.6.3 Derivable Relationships 347<br/>11.6.4 Optional Relationships 348<br/>xvi ■ Contents<br/>11.6.5 Overlapping Foreign Keys 350<br/>11.6.6 Split Foreign Keys 352<br/>11.7 Table and Column Names 354<br/>11.8 Logical Data Model Notations 355<br/>11.9 Summary 357<br/>Chapter 12<br/>Physical Database Design 359<br/>12.1 Introduction 359<br/>12.2 Inputs to Database Design 361<br/>12.3 Options Available to the Database Designer 362<br/>12.4 Design Decisions Which Do Not Affect Program Logic 363<br/>12.4.1 Indexes 363<br/>12.4.2 Data Storage 370<br/>12.4.3 Memory Usage 372<br/>12.5 Crafting Queries to Run Faster 372<br/>12.5.1 Locking 373<br/>12.6 Logical Schema Decisions 374<br/>12.6.1 Alternative Implementation of Relationships 374<br/>12.6.2 Table Splitting 374<br/>12.6.3 Table Merging 376<br/>12.6.4 Duplication 377<br/>12.6.5 Denormalization 378<br/>12.6.6 Ranges 379<br/>12.6.7 Hierarchies 380<br/>12.6.8 Integer Storage of Dates and Times 382<br/>12.6.9 Additional Tables 383<br/>12.7 Views 384<br/>12.7.1 Views of Supertypes and Subtypes 385<br/>12.7.2 Inclusion of Derived Attributes in Views 385<br/>12.7.3 Denormalization and Views 385<br/>12.7.4 Views of Split and Merged Tables 386<br/>12.8 Summary 386<br/>Contents ■ xvii<br/>Part III<br/>Advanced Topics 389<br/>Chapter 13<br/>Advanced Normalization 391<br/>13.1 Introduction 391<br/>13.2 Introduction to the Higher Normal Forms 392<br/>13.2.1 Common Misconceptions 392<br/>13.3 Boyce-Codd Normal Form 394<br/>13.3.1 Example of Structure in 3NF but not in BCNF 394<br/>13.3.2 Definition of BCNF 396<br/>13.3.3 Enforcement of Rules versus BCNF 397<br/>13.3.4 A Note on Domain Key Normal Form 398<br/>13.4 Fourth Normal Form (4NF) and<br/>Fifth Normal Form (5NF) 398<br/>13.4.1 Data in BCNF but not in 4NF 399<br/>13.4.2 Fifth Normal Form (5NF) 401<br/>13.4.3 Recognizing 4NF and 5NF Situations 404<br/>13.4.4 Checking for 4NF and 5NF with the<br/>Business Specialist 405<br/>13.5 Beyond 5NF: Splitting Tables Based on<br/>Candidate Keys 407<br/>13.6 Other Normalization Issues 408<br/>13.6.1 Normalization and Redundancy 408<br/>13.6.2 Reference Tables Produced by Normalization 410<br/>13.6.3 Selecting the Primary Key after Removing Repeating Groups 411<br/>13.6.4 Sequence of Normalization and<br/>Cross-Table Anomalies 414<br/>13.7 Advanced Normalization in Perspective 415<br/>13.8 Summary 416<br/>Chapter 14<br/>Modeling Business Rules 417<br/>14.1 Introduction 417<br/>14.2 Types of Business Rules 418<br/>14.2.1 Data Rules 418<br/>14.2.2 Process Rules 420<br/>xviii ■ Contents<br/>14.2.3 What Rules are Relevant to the Data Modeler? 420<br/>14.3 Discovery and Verification of Business Rules 420<br/>14.3.1 Cardinality Rules 420<br/>14.3.2 Other Data Validation Rules 421<br/>14.3.3 Data Derivation Rules 421<br/>14.4 Documentation of Business Rules 422<br/>14.4.1 Documentation in an E-R Diagram 422<br/>14.4.2 Documenting Other Rules 422<br/>14.4.3 Use of Subtypes to Document Rules 424<br/>14.5 Implementing Business Rules 427<br/>14.5.1 Where to Implement Particular Rules 428<br/>14.5.2 Implementation Options: A Detailed Example 433<br/>14.5.3 Implementing Mandatory Relationships 436<br/>14.5.4 Referential Integrity 438<br/>14.5.5 Restricting an Attribute to a Discrete Set of Values 439<br/>14.5.6 Rules Involving Multiple Attributes 442<br/>14.5.7 Recording Data That Supports Rules 442<br/>14.5.8 Rules That May Be Broken 443<br/>14.5.9 Enforcement of Rules Through Primary Key Selection 445<br/>14.6 Rules on Recursive Relationships 446<br/>14.6.1 Types of Rules on Recursive Relationships 447<br/>14.6.2 Documenting Rules on Recursive Relationships 449<br/>14.6.3 Implementing Constraints on Recursive Relationships 449<br/>14.6.4 Analogous Rules in Many-to-Many Relationships 450<br/>14.7 Summary 450<br/>Chapter 15<br/>Time-Dependent Data 451<br/>15.1 The Problem 451<br/>15.2 When Do We Add the Time Dimension? 452<br/>15.3 Audit Trails and Snapshots 452<br/>15.3.1 The Basic Audit Trail Approach 453<br/>15.3.2 Handling Nonnumeric Data 458<br/>15.3.3 The Basic Snapshot Approach 458<br/>15.4 Sequences and Versions 462<br/>15.5 Handling Deletions 463<br/>15.6 Archiving 463<br/>Contents ■ xix<br/>15.7 Modeling Time-Dependent Relationships 464<br/>15.7.1 One-to-Many Relationships 464<br/>15.7.2 Many-to-Many Relationships 466<br/>15.7.3 Self-Referencing Relationships 468<br/>15.8 Date Tables 469<br/>15.9 Temporal Business Rules 469<br/>15.10 Changes to the Data Structure 473<br/>15.11 Putting It into Practice 473<br/>15.12 Summary 474<br/>Chapter 16<br/>Modeling for Data Warehouses and<br/>Data Marts 475<br/>16.1 Introduction 475<br/>16.2 Characteristics of Data Warehouses and Data Marts 478<br/>16.2.1 Data Integration: Working with Existing Databases 478<br/>16.2.2 Loads Rather Than Updates 478<br/>16.2.3 Less Predictable Database “Hits” 479<br/>16.2.4 Complex Queries—Simple Interface 479<br/>16.2.5 History 480<br/>16.2.6 Summarization 480<br/>16.3 Quality Criteria for Warehouse and Mart Models 480<br/>16.3.1 Completeness 480<br/>16.3.2 Nonredundancy 481<br/>16.3.3 Enforcement of Business Rules 482<br/>16.3.4 Data Reusability 482<br/>16.3.5 Stability and Flexibility 482<br/>16.3.6 Simplicity and Elegance 483<br/>16.3.7 Communication Effectiveness 483<br/>16.3.8 Performance 483<br/>16.4 The Basic Design Principle 483<br/>16.5 Modeling for the Data Warehouse 484<br/>16.5.1 An Initial Model 484<br/>16.5.2 Understanding Existing Data 485<br/>16.5.3 Determining Requirements 485<br/>16.5.4 Determining Sources and Dealing with Differences 485<br/>16.5.5 Shaping Data for Data Marts 487<br/>xx ■ Contents<br/>16.6 Modeling for the Data Mart 488<br/>16.6.1 The Basic Challenge 488<br/>16.6.2 Multidimensional Databases, Stars and Snowflakes 488<br/>16.6.3 Modeling Time-Dependent Data 494<br/>16.7 Summary 496<br/>Chapter 17<br/>Enterprise Data Models and Data Management 499<br/>17.1 Introduction 499<br/>17.2 Data Management 500<br/>17.2.1 Problems of Data Mismanagement 500<br/>17.2.2 Managing Data as a Shared Resource 501<br/>17.2.3 The Evolution of Data Management 501<br/>17.3 Classification of Existing Data 503<br/>17.4 A Target for Planning 504<br/>17.5 A Context for Specifying New Databases 506<br/>17.5.1 Determining Scope and Interfaces 506<br/>17.5.2 Incorporating the Enterprise Data Model in the Development<br/>Life Cycle 506<br/>17.6 Guidance for Database Design 508<br/>17.7 Input to Business Planning 508<br/>17.8 Specification of an Enterprise Database 509<br/>17.9 Characteristics of Enterprise Data Models 511<br/>17.10 Developing an Enterprise Data Model 512<br/>17.10.1 The Development Cycle 512<br/>17.10.2 Partitioning the Task 513<br/>17.10.3 Inputs to the Task 514<br/>17.10.4 Expertise Requirements 515<br/>17.10.5 External Standards 515<br/>17.11 Choice, Creativity, and Enterprise Data Models 516<br/>17.12 Summary 517<br/>Further Reading 519<br/>Index 525</p><p>学习数据挖掘应该可以帮上忙。</p><br/>(/body)(price)0(/price)(transport)1(/transport)[/payto]