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About the Webinar
Good data is like good water: best served fresh, and ideally well-filtered. Data Management strategies can produce tremendous procedural improvements and increased profit margins across the board, but only if the data being managed is of high quality. Determining how Data Quality should be engineered provides a useful framework for utilizing Data Quality management effectively in support of business strategy. This, in turn, allows for speedy identification of business problems, delineation between structural and practice-oriented defects in Data Management, and proactive prevention of future issues. Organizations must realize what it means to utilize Data Quality engineering in support of business strategy. This webinar will illustrate how organizations with chronic business challenges can often trace the root of the problem to poor Data Quality. Showing how Data Quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from reoccurring.
- Help you understand foundational Data Quality concepts for improving Data Quality at your organization
- Demonstrate how chronic business challenges for organizations are often rooted in poor Data Quality
- Share case studies illustrating the hallmarks and benefits of Data Quality success
About the Speaker
Peter Aiken, PhD
Professor of Information Systems, VCU and Founder, Anything Awesome
Peter Aiken, an acknowledged Data Management (DM) authority, is an Associate Professor at Virginia Commonwealth University, past President of DAMA International, and Associate Director of the MIT International Society of Chief Data Officers. For more than 35 years, Peter has learned from working with hundreds of Data Management practices in 30 countries. Among his 10 books are the first on CDOs (the case for data leadership), the first describing the use of monetization data for profit/good, and the first on modern strategic data thinking. International recognition has resulted in an intensive schedule of events worldwide. Peter also hosts the longest-running DM webinar series (hosted by dataversity.net). From 1999 (before Google, before data was big, and before Data Science), he founded Data Blueprint, a consulting firm that helped more than 150 organizations leverage data for profit, improvement, competitive advantage, and operational efficiencies. His latest venture is Anything Awesome.