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 a high quality. Determining how Data Quality should be engineered provides a useful framework for utilizing Data Quality Management effectively in support of business strategy, which 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 often can 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 re-occurring.

Learning Objectives:

• Understand foundational Data Quality concepts based on the DAMA Guide to Data Management Book of Knowledge (DAMA DMBOK), as well as guiding principles, best practices, and steps for improving Data Quality at your organization
  
• Recognize 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
  

Peter Aiken

Founding Director, Data Blueprint

Peter Aiken is an acknowledged Data Management (DM) authority. As a practicing data consultant, professor, author, and researcher, he has studied DM for more than 30 years. International recognition has come from assisting more than 150 organizations in 30 countries, including some of the world's most important. He is a dynamic presence at events and author of 10 books and multiple publications, including his latest on Data Strategy. Peter also hosts the longest running webinar series dedicated to DM (hosted by dataversity.net). In 1999, he founded Data Blueprint, a consulting firm that helps organizations leverage data for profit, improvement, competitive advantage, and operational efficiencies.  He is also Associate Professor of Information Systems at Virginia Commonwealth University (VCU), past President of the International Data Management Association (DAMA-I), and Associate Director of the MIT International Society of Chief Data Officers.