Dec 10 Data-Ed Webinar: Data Management Best Practices

DATE: December 10, 2024

TIME: 2:00 PM – 3:30 PM Eastern / 11:00 AM – 12:30 PM Pacific

PRICE: Free to all attendees

This webinar is sponsored by:

About the Webinar

It is clear that Data Management best practices exist – and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:

Their current Data Management practices
Strengths that should be leveraged
Remediation opportunities

About the Speaker

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.

Data Topics