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Today, companies capture and store tremendous amounts of information about every aspect of their business: their customers, partners, vendors, markets, and more. But with the rise in the quantity of information has come a corresponding decrease in its quality–a problem businesses recognize and are working feverishly to solve.
Enterprise Knowledge Management: The Data Quality Approach presents an easily adaptable methodology for defining, measuring, and improving data quality. Author David Loshin begins by presenting an economic framework for understanding the value of data quality, then proceeds to outline data quality rules and domain-and mapping-based approaches to consolidating enterprise knowledge. Written for both a managerial and a technical audience, this book will be indispensable to the growing number of companies committed to wresting every possible advantage from their vast stores of business information.
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Today, companies capture and store tremendous amounts of information about every aspect of their business: their customers, partners, vendors, markets, and more. But with the rise in the quantity of information has come a corresponding decrease in its quality–a problem businesses recognize and are working feverishly to solve.
Enterprise Knowledge Management: The Data Quality Approach presents an easily adaptable methodology for defining, measuring, and improving data quality. Author David Loshin begins by presenting an economic framework for understanding the value of data quality, then proceeds to outline data quality rules and domain-and mapping-based approaches to consolidating enterprise knowledge. Written for both a managerial and a technical audience, this book will be indispensable to the growing number of companies committed to wresting every possible advantage from their vast stores of business information.