Data quality has become increasingly important to many firms as they build data warehouses and focus more on customer relationship management. This is especially true in the health care field where cost pressures and the desire to improve patient care drive efforts to integrate and clean organizational data. This paper reviews earlier work on data quality and extends it by providing a process model of architected data environments. This model allow practitioners and researchers to focus on processes that generate data quality problems. The paper also describes how the model was used in a real world health care organization and what implications there are for practitioners and researchers. © 2001 IEEE.
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