12 Guidelines for Success in Data Quality Projects

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About the Paper

From years of data quality initiatives, hundreds of case studies, and research by industry experts, a number of common data quality success factors have emerged. This paper discusses key characteristics of data quality initiatives and provides actionable guidelines to help make your project a success, from conception through implementation and tracking your ROI. Readers will learn how to:

Quantify the effect of poor data quality on the organization
Prioritize projects for faster ROI
Gain buy-in, from employees through senior management

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Data Education for Business and IT Professionals

12 Guidelines for Success in Data Quality Projects

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About the Paper