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About Data Quality Assessment
Product Description Imagine a group of prehistoric hunters armed with stone-tipped spears. Their primitive weapons made hunting large animals, such as mammoths, dangerous work. Over time, however, a new breed of hunters developed. They would stretch the skin of a previously killed mammoth on the wall and throw their spears, while observing which spear, thrown from which angle and distance, penetrated the skin the best. The data gathered helped them make better spears and develop better hunting strategies. Quality data is the key to any advancement, whether it’s from the Stone Age to the Bronze Age. Or from the Information Age to whatever Age comes next. The success of corporations and government institutions largely depends on the efficiency with which they can collect, organize, and utilize data about products, customers, competitors, and employees. Fortunately, improving your data quality doesn't have to be such a mammoth task. DATA QUALITY ASSESSMENT is a must read for anyone who needs to understand, correct, or prevent data quality issues in their organization. Skipping theory and focusing purely on what is practical and what works, this text contains a proven approach to identifying, warehousing, and analyzing data errors – the first step in any data quality program. Master techniques in: Data profiling and gathering metadata Identifying, designing, and implementing data quality rules Organizing rule and error catalogues Ensuring accuracy and completeness of the data quality assessment Constructing the dimensional data quality scorecard Executing a recurrent data quality assessment Review DATA QUALITY ASSESSMENT is an excellent book and a must read for any data quality professional. Arkady packs years of experience in data quality into comprehensive step-by-step instructions for practitioners of all levels. --R. Michael Levin, Sr. Database Architect, Lockheed Martin DATA QUALITY ASSESSMENT is an excellent book and a must read for any data quality professional. Arkady packs years of experience in data quality into comprehensive step-by-step instructions for practitioners of all levels. --R. Michael Levin, Sr. Database Architect, Lockheed Martin About the Author Arkady Maydanchik is a recognized practitioner, author, and educator in the field of data quality and information integration. He is a frequent speaker at conferences and seminars, and teaches data quality courses through the Data Warehousing Institute and through his company, Data Quality Group LLC.
