Journey to Data Quality | 
enlarge | Authors: Yang W. Lee, Leo L. Pipino, James D. Funk, Richard Y. Wang Publisher: The MIT Press Category: Book
List Price: $36.00 Buy New: $23.93 You Save: $12.07 (34%)
New (21) Used (7) from $19.17
Sales Rank: 676965
Media: Hardcover Number Of Items: 1 Pages: 240 Shipping Weight (lbs): 0.9 Dimensions (in): 9.1 x 6.1 x 0.9
ISBN: 0262122871 Dewey Decimal Number: 658.4038 EAN: 9780262122870 ASIN: 0262122871
Publication Date: October 1, 2006 Availability: Usually ships in 1-2 business days Shipping: Expedited shipping available Condition: BRAND NEW!. Hardcover. Comes w/Dust Cover. Proven Seller with Great Service!. Ships fast! Choose Expedited shipping for fastest delivery!
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Product Description All organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level?installing the latest software or developing an expensive data warehouse?solve the basic problem of bad data quality practices. Journey to Data Quality offers a roadmap that can be used by practitioners, executives, and students for planning and implementing a viable data and information quality management program. This practical guide, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools, and techniques necessary to meet them. The authors, all leaders in the data quality field for many years, discuss how to make the economic case for data quality and the importance of getting an organization's leaders on board. They outline different approaches for assessing data, both subjectively (by users) and objectively (using sampling and other techniques). They describe real problems and solutions, including efforts to find the root causes of data quality problems at a healthcare organization and data quality initiatives taken by a large teaching hospital. They address setting company policy on data quality and, finally, they consider future challenges on the journey to data quality.
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