Best practices for designing and implementing sustainable, long-term data quality programs |
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| 21 Jul 2008 | SeachDataManagement.com |
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The volume of data coming into organizations is growing exponentially. Effective data quality management must be sustainable and designed for the long term. In this expert Webcast, discover best practices for designing and implementing data quality management programs that will stand the test of time and learn:
- Best practices for successfully designing and implementing data quality management programs from start to finish.
- Why periodic batch cleansing is no longer enough for most organizations to maintain data quality for the long term.
- Secrets of successful data quality management programs, common mistakes and how to avoid them.
About the speaker: William is partner, information management at Lucidity Consulting Group. He functions as strategist, lead enterprise information architect and program manager for complex, high-volume, full life-cycle implementations worldwide -- utilizing the disciplines of data warehousing, master data management (MDM), business intelligence (BI), data quality and operational BI. McKnight has authored more than 150 articles and white papers and given over 150 international keynotes and public seminars. He is a former IT VP of a Fortune company, a former engineer of DB2 at IBM and holds an MBA.
| Best practices for designing and implementing sustainable, long-term data quality programs | |
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Learn best practices for designing and implementing data quality management programs, in this expert Webcast with William McKnight.
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