Date/Time Date(s) - 10/09/20242:00 pm - 3:30 pm
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 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:
Peter Aiken, PhD
Professor of Information Systems, VCU and Founder, Anything Awesome
Peter Aiken, Ph.D. is an acknowledged Data Management authority, an associate professor at Virginia Commonwealth University, president of DAMA International, and associate director of the MIT International Society of Chief Data Officers. For more than 40 years, Peter has learned from working with hundreds of Data Management practices in more than 30 countries. Among his 12 books are the first on making the case for data leadership (CDOs), the first focusing on data monetization and modern strategic data thinking, and the first to objectively specify what it means to be data-literate. International recognition has resulted from these and a (pre-Covid-19) intensive worldwide events schedule. Peter also hosts the longest-running Data Management webinar series on dataversity.net. Before Google, before data was big, and before Data Science, Peter founded several organizations that have helped more than 200 businesses leverage data – specific savings have been measured at more than $1.5 billion. His latest venture is Anything Awesome.