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. |
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. |
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. |
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. |
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 |
6.1 | ER diagram showing new relationships to the time dimension. |
6.2 | Logical model of part of the Wine Club |
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. |
8.1 | Development abstraction shown as a roadmap. |
9.1 | Classic waterfall approach. |
9.2 | Example project team structure. |
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. |
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