ABSTRACT
In competitive financial market, every day brings new challenges for customer acquisition and retention. To stay ahead, financial services companies are turning to decision support solutions to help identify and manage their customer relationships. Solutions such as data warehouses or data marts provide a solid foundation of accurate information upon which they can base their decisions. Building data quality into a data warehouse involves six key elements: parsing, correction, enhancement, standardization, matching, and consolidation. The chapter helps IT professionals discover the principles and inherent problems of data quality and data consolidation, and the available solutions to help professionals manage them. For the most accurate information to support IT professionals' financial services business, they will need to incorporate data quality into each critical step — extraction, transformation, consolidation, and maintenance. Data quality is especially important to accurate consolidation because it allows them to recognize and understand customer relationships.
