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Engineering Data Quality – A Framework for Effective Data Management

DATE: September 9, 2025

TIME: 2:00 PM - 3:00 PM Eastern / 11:00 AM - 12:00 PM Pacific

PRICE: Free to all attendees

About the Webinar

High-quality data is essential for effective data management strategies, which can lead to significant procedural improvements and increased profit margins. Engineering data quality provides a framework for utilizing data quality management effectively in support of business strategy. This approach allows for the quick identification of business problems, differentiation between structural and practice-oriented defects in data management, and proactive prevention of future issues. Organizations must understand the importance of utilizing data quality engineering to support their business strategy. 

This webinar will demonstrate how chronic business challenges often stem from poor data quality and will illustrate how engineering data quality provides a useful framework for developing an effective approach. This, in turn, enables organizations to quickly identify business problems and data issues caused by structural or practice-oriented defects, preventing their recurrence. 

Learning objectives: 

  • 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
Professor of Information Systems, VCU and Founder, Anything Awesome

insert-image.jpgPeter 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 13 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.







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