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IAIDQ IDQ Webinars: with Danette McGilvray 2009-01-14

Topic:

The 12 Dimensions of Data Quality

Abstract:

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.

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Recording:

Speaker:

Danette McGilvray

Danette McGilvray is President and Principal of Granite Falls Consulting, Inc., a firm specializing in information quality management and data governance. Projects include enterprise data quality services, data warehousing strategies, and best practices for large-scale ERP data migrations for Fortune 500 organizations. Danette is an invited speaker at conferences throughout the US and Europe. Her previous experience as a leader of enterprise data quality within a company and now working with clients in various industries, gives her understanding of the information quality challenges faced daily by organizations. She is the author of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Morgan Kaufmann, 2008).

 

Email to danette [AT] gfalls [dot] com

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