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ABSTRACT:
Data quality has often been isolated as a separate silo in the organization, rather than fully integrated into the way business is conducted. However, most operations and businesses run on information and data that must be of high quality. Data quality does not just relate to the data, but rather to actual business impacts.
Read this white paper by industry expert David Loshin to explore data quality impacts, how it relates to business issues and how to integrate data quality monitoring into operational systems. Also, four major topics will be addressed: understanding the business impacts of poor data quality, identifying data quality dimensions, defining data quality business rules both for monitoring and measuring, and supporting data quality management.
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Author
David Loshin
President
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Knowledge Integrity, Inc.
David Loshin is the president of Knowledge Integrity, Inc., a consulting company focusing on customized information management solutions including information quality consulting and training, business intelligence, metadata, and data standards management. Loshin is an industry thought leader and one of Knowledge Integrity’s most recognized experts in information management. In addition, he is a SearchDataManagement.com expert. He writes for many industry publications, creates and teaches courses for the Data Warehousing Institute and other venues, and regularly presents at the annual DAMA/Metadata conference. Loshin is the author of Enterprise Knowledge Management: The Data Quality Approach, which describes a revolutionary strategy for defining, managing, and implementing business rules affecting data quality management. His other book, Business Intelligence: The Savvy Manager’s Guide, has been hailed as a leading business intelligence resource.
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