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

Data Quality Assessment

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 itâ€™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 â€“ 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

Country	USA
Author	Arkady Maydanchik
Binding	Kindle Edition
Edition	First
EISBN	9781935504429
Format	Kindle eBook
IsAdultProduct
Label	Technics Publications, LLC
Manufacturer	Technics Publications, LLC
NumberOfPages	337
PublicationDate	2012-07-01
Publisher	Technics Publications, LLC
ReleaseDate	2012-07-01
Studio	Technics Publications, LLC

Data Quality Assessment

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