| 1.1 | Just who are our best customers? |
| 1.2 | CRM in an organization. |
| 1.3 | The components of CRM. |
| 1.4 | The number of communication channels is growing. |
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| 2.1 | Fragment of data model for the Wine Club. |
| 2.2 | Three-dimensional data cube. |
| 2.3 | Wine sales dimensional model for the Wine Club. |
| 2.4 | Data model showing multiple join paths. |
| 2.5 | The main components of a data warehouse system. |
| 2.6 | General-state transition diagram. |
| 2.7 | State transition diagram for the orders process. |
| 2.8 | Star schema showing the relationships between facts and dimensions. |
| 2.9 | Stratification of the data. |
| 2.10 | Snowflake schema for the sale of wine. |
| 2.11 | Levels of summarization in a data warehouse. |
| 2.12 | Modified data warehouse structure incorporating summary navigation and data mining. |
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| 3.1 | Star schema for the Wine Club. |
| 3.2 | Third normal form version of the Wine Club dimensional model. |
| 3.3 | Confusing and intimidating hierarchy. |
| 3.4 | Common organizational hierarchy. |
| 3.5 | Star schema for the Wine Club. |
| 3.6 | Sharing information. |
| 3.7 | General model for customer details. |
| 3.8 | General model for a customer with changing circumstances. |
| 3.9 | Example model showing customer with changing circumstances. |
| 3.10 | The general model extended to include behavior. |
| 3.11 | The example model extended to include behavior. |
| 3.12 | General conceptual model for a customer-centric data warehouse. |
| 3.13 | Wine Club customer changing circumstances. |
| 3.14 | Wine Club customer behavior. |
| 3.15 | Derived segment examples for the Wine Club. |
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| 4.1 | Fragment of operational data model. |
| 4.2 | Operational model with additional sales fact table. |
| 4.3 | Sales hierarchy. |
| 4.4 | Sales hierarchy with sales table attached. |
| 4.5 | Sales hierarchy showing altered relationships. |
| 4.6 | Sales hierarchy with intersection entities. |
| 4.7 | Sales hierarchy with data. |
| 4.8 | Simple general business hierarchy. |
| 4.9 | Graphical representation of temporal functions. |
| 4.10 | Types of temporal query. |
| 4.11 | Traditional resolution of m:n relationships. |
| 4.12 | Representation of temporal attributes by attaching them to the dimension. |
| 4.13 | Representation of temporal hierarchies by attaching them to the facts. |
| 4.14 | Representation of temporal attributes by attaching them to the facts. |
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| 5.1 | Example of a two-dimensional report. |
| 5.2 | Example of a three-dimensional cube. |
| 5.3 | Simple multidimensional dot model. |
| 5.4 | Representation of the Wine Club using a dot model. |
| 5.5 | Customer-centric dot model. |
| 5.6 | Initial dot model for the Wine Club. |
| 5.7 | Refined dot model for the Wine Club. |
| 5.8 | Dot modeling worksheet showing Wine Club sales behavior. |
| 5.9 | Example of a hierarchy |
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| 6.1 | ER diagram showing new relationships to the time dimension. |
| 6.2 | Logical model of part of the Wine Club |
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| 7.1 | The EASI data architecture. |
| 7.2 | Metadata model for validation. |
| 7.3 | Integration layer. |
| 7.4 | Additions to the metadata model to include the source mapping layer. |
| 7.5 | Metadata model for the VIM layer. |
| 7.6 | Customer nonchanging details. |
| 7.7 | The changing circumstances part of the GCM. |
| 7.8 | Behavioral model for the Wine Club. |
| 7.9 | Data model for derived segments. |
| 7.10 | Daily partitions. |
| 7.11 | Duplicated input. |
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| 8.1 | Development abstraction shown as a roadmap. |
| 9.1 | Classic waterfall approach. |
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| 9.2 | Example project team structure. |
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| 10.1 | Extraction, transformation, and load processing. |
| 10.2 | Typical OLAP architecture. |
| 10.3 | Descriptive field distribution. |
| 10.4 | Numeric field distribution using a histogram. |
| 10.5 | Web plot that relates gender to regions . |
| 10.6 | Rule induction for wine sales. |
| 10.7 | Example of a multiphase campaign. |