Data Quality in Utilities: Concepts and Best Practices
Data quality is a large and complex field with many dimensions. Every data quality practitioner needs a foundation of concepts, principles, and terminology that are common in quality management. Building upon that foundation, they need to understand how quality management concepts and principles are applied to data, as well as the language and terminology that specifically apply to data quality. The importance of data quality in the Utility industry is rapidly growing as new use cases for analytics are identified and pursued.
Jed SummertonConsultant & Adjunct Professor
Jed Summerton is an analytic leader and practitioner with over 40 years of experience in commercial businesses, with a 50/50 mix of internal roles and consulting. As an internal leader he served as VP of Analytics to companies such as DaVita, TerumoBCT, Level 3 Communications (now called Lumen) and General Electric. As a consultant his clients include Lumen, GE, Xerox, PetSmart, Newmont Mining, McKesson, Michelin, Merrill Lynch and Technicolor. Early in his career he worked for NASA on space shuttle operations, where he learned that “NASA” really means “Never A Simple Answer.”
Jed also serves as an adjunct professor in the department of Business Information and Analytics in the Daniels College of Business since 2010, and he chairs the department’s advisory board. He teaches in the graduate and undergraduate programs in analytics, in the online and professional MBA programs, and in Executive Education.
Mark PecoIndependent Consultant & Educator