Automated Data Warehousing for Rule-based CRM Systems

This paper proposes a novel way of automatically developing data warehouse configuration in rule-based CRM systems. Rule-based CRM systems assume that marketing activities are represented as a set of IF-THEN rules. Currently, to provide good quality CRM functionalities, CRM systems seek to combine conventional CRM methodologies with data warehousing technology. A data warehouse can be abstractly seen as a set of materialized views. Selecting views for materialization in a data warehouse is one of the important decision-making tasks in its design. However, there are few facilities in CRM systems with respect to data warehouse design that alleviate the problems associated with data schema maintenance. Given a set of campaign rules expressing marketing strategies, the proposed method generates data warehouse configuration (including database schema and indexing constraint) that can satisfy all the input rules. Our method begins on the premise that data warehouse configuration can be reversibly extracted from marketing campaign rules. This method includes algorithms for database schema generation, indexing constraint generation, schema normalization for removing data redundancies, and OLAP (On-Line Analytic Processing) query generation.