Customer-Centric Data Warehouses
Chan (2003) describes the construction of data warehouses using the enterprise model. The CRM enterprise
model can be used to develop customer-centric data warehouses and data marts which provide the data for CRM
analytics. The analytic data model and the analytic function model provide the conceptual framework for the
customer data warehouses and data marts. The analytic data model can be constructed from the enterprise data
model by associating data entities along subject areas based on the requirements defined in the analytic function
model. For example, the analytic function of determining what products to cross-sell to a specific segment of
customers requires data from many sales transactions over a long period of time for a particular segment of
customers covering many product lines. Techniques in dimensional modeling can be deployed to construct the
analytic data model (Todman 2001). Data from customer interactions are captured in various transactional systems.
Transactional data in conjunction with legacy and external data are extracted, transformed and loaded (ETL) into the
target data warehouses or operational data stores (ODS) that provide the data feeds for the target data warehouses
and data marts. As illustrated in Figure 4, customer data warehouses and data marts across the enterprise are mapped
to their respective data sources which are logically connected to the conceptual CRM model. The conceptual CRM
model thus provides the integrated framework for customer data warehouses and data marts across the enterprise.