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Despite the general consensus of the importance of data quality, many organizations are not aware that the lack of data quality is one of the main sources of loss of time, money and opportunities in the business environment. Even in organizations with this level of conscience, in many of them there is not a consolidated and applicable methodology in order to guarantee a continuous improvement in the data quality. The failure in many business iniciatives has been caused for wrong strategical decisions, based in low quality organizational data. Many organizations incorporate, on their daily routine, reactive activities like correction and order reprocessing, and the unavoidable result is the waste of resources. The objective of this article is to present the several aspects involved in data quality and show an implementation methodology for continuous improvement of data quality, mainly for data warehouses. In this article, are showed the impacts suffered by organizations caused by low quality data. and an introduction to the concept of dataquality. Subsequently, is presented an itinerary step-by-step of how to implement and maintain a continuous dataquality improvement program for data warehouses. This itinerary contains technical and political issues to implement the change, and is also useful for data quality improvement programs in transactional databases. Afterwards, is presented an practical case of data quality program improvement in a large organization, showing is targets, challenges and observed results. Finally is presented a conclusion and recommendations for a data quality implementation program.

Data Quality; Data Warehouse.