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| Acknowledgments | |
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| About the Authors | |
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| Concepts | |
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| Introduction | |
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| Overview of Business Intelligence | |
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| BI Architecture | |
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| What Is a Data Warehouse? | |
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| Role and Purpose of the Data Warehouse | |
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| The Corporate Information Factory | |
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| The Multipurpose Nature of the Data Warehouse | |
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| Types of Data Marts Supported | |
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| Types of BI Technologies Supported | |
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| Characteristics of a Maintainable Data Warehouse Environment | |
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| The Data Warehouse Data Model | |
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| Nonredundant | |
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| Stable | |
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| Consistent | |
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| Flexible in Terms of the Ultimate Data Usage | |
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| The Codd and Date Premise | |
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| Impact on Data Mart Creation | |
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| Summary | |
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| Fundamental Relational Concepts | |
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| Why Do You Need a Data Model? | |
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| Relational Data-Modeling Objects | |
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| Subject | |
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| Entity | |
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| Element or Attribute | |
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| Relationships | |
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| Types of Data Models | |
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| Subject Area Model | |
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| Business Data Model | |
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| System Model | |
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| Technology Model | |
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| Relational Data-Modeling Guidelines | |
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| Guidelines and Best Practices | |
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| Normalization | |
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| Normalization of the Relational Data Model | |
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| First Normal Form | |
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| Second Normal Form | |
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| Third Normal Form | |
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| Other Normalization Levels | |
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| Summary | |
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| Model Development | |
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| Understanding the Business Model | |
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| Business Scenario | |
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| Subject Area Model | |
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| Considerations for Specific Industries | |
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| Subject Area Model Development Process | |
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| Subject Area Model for Zenith Automobile Company | |
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| Business Data Model | |
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| Business Data Development Process | |
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| Summary | |
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| Developing the Model | |
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| Methodology | |
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| Select the Data of Interest | |
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| Add Time to the Key | |
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| Add Derived Data | |
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| Determine Granularity Level | |
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| Summarize Data | |
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| Merge Entities | |
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| Create Arrays | |
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| Segregate Data | |
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| Summary | |
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| Creating and Maintaining Keys | |
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| Business Scenario | |
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| Inconsistent Business Definition of Customer | |
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| Inconsistent System Definition of Customer | |
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| Inconsistent Customer Identifier among Systems | |
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| Inclusion of External Data | |
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| Customers Uniquely Identified Based on Role | |
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| Customer Hierarchy Not Depicted | |
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| Data Warehouse System Model | |
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| Inconsistent Business Definition of Customer | |
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| Inconsistent System Definition of Customer | |
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| Inconsistent Customer Identifier among Systems | |
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| Absorption of External Data | |
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| Customers Uniquely Identified Based on Role | |
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| Customer Hierarchy Not Depicted | |
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| Data Warehouse Technology Model | |
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| Key from the System of Record | |
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| Key from a Recognized Standard | |
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| Surrogate Key | |
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| Dimensional Data Mart Implications | |
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| Differences in a Dimensional Model | |
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| Maintaining Dimensional Conformance | |
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| Summary | |
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| Modeling the Calendar | |
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| Calendars in Business | |
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| Calendar Types | |
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| Other Fiscal Calendars | |
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| Calendar Elements | |
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| Calendar Time Span | |
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| Time and the Data Warehouse | |
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| The Nature of Time | |
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| Standardizing Time | |
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| Data Warehouse System Model | |
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| Date Keys | |
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| Case Study: Simple Fiscal Calendar | |
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| Analysis | |
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| A Simple Calendar Model | |
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| Case Study: A Location Specific Calendar | |
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| Analysis | |
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| The GOSH Calendar Model | |
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| Delivering the Calendar | |
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| Case Study: A Multilingual Calendar | |
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| Analysis | |
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| Storing Multiple Languages | |
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| Handling Different Date Presentation Formats | |
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| Delivering Multiple Languages | |
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| Case Study: Multiple Fiscal Calendars | |
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| Analysis | |
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| Expanding the Calendar | |
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| Case Study: Seasonal Calendars | |
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| Analysis | |
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| Seasonal Calendar Structures | |
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| Delivering Seasonal Data | |
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| Summary | |
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| Modeling Hierarchies | |
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| Hierarchies in Business | |
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| The Nature of Hierarchies | |
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| Hierarchy Depth | |
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| Hierarchy Parentage | |
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| Hierarchy Texture | |
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| History | |
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| Summary of Hierarchy Types | |
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| Case Study: Retail Sales Hierarchy | |
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| Analysis of the Hierarchy | |
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| Implementing the Hierarchies | |
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| Case Study: Sales and Capacity Planning | |
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| Analysis | |
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| The Product Hierarchy | |
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| The Customer Hierarchy | |
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| Case Study: Retail Purchasing | |
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| Analysis | |
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| Implementing the Business Model | |
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| Case Study: The Combination Pack | |
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| Analysis | |
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| Adding a Bill of Materials | |
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| Publishing the Data | |
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| Transforming Structures | |
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| Making a Recursive Tree | |
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| Flattening a Recursive Tree | |
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| Summary | |
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| Modeling Transactions | |
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| Business Transactions | |
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| Business Use of the Data Warehouse | |
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| Average Lines per Transaction | |
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| Business Rules Concerning Changes | |
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| Application Interfaces | |
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| Snapshot Interfaces | |
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| Delta Interfaces | |
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| Database Transaction Logs | |
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| Delivering Transaction Data | |
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| Case Study: Sales Order Snapshots | |
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| Transforming the Order | |
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| Complete Snapshot Capture | |
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| Change Snapshot Capture | |
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| Change Snapshot with Delta Capture | |
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| Load Processing | |
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| Case Study: Transaction Interface | |
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| Modeling the Transactions | |
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| Processing the Transactions | |
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| Summary | |
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| Data Warehouse Optimization | |
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| Optimizing the Development Process | |
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| Optimizing Design and Analysis | |
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| Optimizing Application Development | |
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| Optimizing the Database | |
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| Data Clustering | |
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| Table Partitioning | |
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| Enforcing Referential Integrity | |
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| Index-Organized Tables | |
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| Indexing Techniques | |
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| Conclusion | |
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| Optimizing the System Model | |
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| Vertical Partitioning | |
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| Denormalization | |
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| Subtype Clusters | |
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| Summary | |
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| Operation and Management | |
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| Accommodating Business Change | |
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| The Changing Data Warehouse | |
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| Reasons for Change | |
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| Controlling Change | |
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| Implementing Change | |
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| Modeling for Business Change | |
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| Assuming the Worst Case | |
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| Imposing Relationship Generalization | |
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| Using Surrogate Keys | |
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| Implementing Business Change | |
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| Integrating Subject Areas | |
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| Adding Subject Areas | |
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| Summary | |
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| Maintaining the Models | |
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| Governing Models and Their Evolution | |
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| Subject Area Model | |
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| Business Data Model | |
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| System Data Model | |
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| Technology Data Model | |
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| Synchronization Implications | |
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| Model Coordination | |
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| Subject Area and Business Data Models | |
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| Business and System Data Models | |
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| System and Technology Data Models | |
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| Managing Multiple Modelers | |
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| Roles and Responsibilities | |
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| Collision Management | |
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| Summary | |
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| Deploying the Relational Solution | |
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| Data Mart Chaos | |
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| Why Is It Bad? | |
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| Criteria for Being in-Architecture | |
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| Migrating from Data Mart Chaos | |
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| Conform the Dimensions | |
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| Create the Data Warehouse Data Model | |
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| Create the Data Warehouse | |
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| Build New Data Marts Only "In-Architecture"--Leave Old Marts Alone | |
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| Build the Architecture from One Data Mart | |
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| Choosing the Right Migration Path | |
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| Summary | |
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| Comparison of Data Warehouse Methodologies | |
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| The Multidimensional Architecture | |
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| The Corporate Information Factory Architecture | |
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| Comparison of the CIF and MD Architectures | |
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| Scope | |
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| Perspective | |
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| Data Flow | |
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| Volatility | |
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| Flexibility | |
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| Complexity | |
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| Functionality | |
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| Ongoing Maintenance | |
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| Summary | |
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| Glossary | |
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| Recommended Reading | |
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| Index | |