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Data Quality: The Accuracy Dimension Review by K. Ambrose
Practical techniques that will have an impact on your ETL
Concepts and technical approaches for analyzing and improving the usefullness of source data are presented in a well organized and logical sequence. Not quite a roadmap/algorithm for achieving data quality; it's balanced a little more on the conceptual side. The techniques and concepts presented are ones you _will_ want to begin using if you have any data quality issues in your source data (and who doesn't), I guarantee that. As a working ETL developer referencing disparate, low quality data, this book has had an impact on our approach, our results, and our project. Short and to the point, it's an easy study also!