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IDQ Webinars: with Danette McGilvray 2009-01-14


The 12 Dimensions of Data Quality


Data quality dimensions are aspects or features of quality. They provide a way to measure and manage the quality of data and information. Each data quality dimension requires different techniques, tools, and processes to measure it. This results in varying levels of time, money, and human resources to complete the assessment process or manage the quality of that dimension. You can better scope your projects or individual work by understanding the effort required to assess or manage each of the dimensions and choose the one that fits your needs. Join our expert Dannette McGilvray and IDQ Webinars hosts Piyush Malik and Tony O'Brien to learn about the 12 dimensions and how they can support your data quality efforts.



About the Author

Danette McGilvray's photo

Danette McGilvray is president and principal of Granite Falls Consulting, Inc., a firm that helps organizations increase their success by addressing the information quality and data governance aspects of their business efforts. She also emphasizes communication and the human aspect of information quality and governance.

Danette is the author of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Morgan Kaufmann, 2008). An internationally respected expert, her Ten Steps™ approach to information quality has been embraced as a proven method for creating and improving data quality in the enterprise. The Chinese-language edition is available and her book is used as a textbook in university graduate programs. Danette was the 2013 recipient of IAIDQ’s Distinguished Member Award in recognition of her outstanding contributions to the field of information and data quality.

She can be reached via email at danette [AT] gfalls [dot] com

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