Monday, June 5, 2023
08:30 AM - 11:45 AM
Intermediate
90 percent, or more, of organizational data challenges, are people and processes – not technology challenges! Strengthening our focus on non-technology aspects of data governance will be seen as crucial. A conscious effort to spend at least as much time on ethics as technology is an excellent place to start. Like ubiquitous "safety minutes," periodic ethics discussions will help prevent surprises, introduce vocabulary, and, most importantly, keep the first discussion of organizational ethics from occurring in the middle of a data crisis.
This program will present information you can take away and use to start ethical discussions as part of your data program. Much of the information is transferred via a series of workshop discussions describing "incidents." Understanding how they were discovered, their handling, and lessons learned–leading to specific operational changes/improvements. The material focuses on people and process issues encountered with each incident. We believe these illustrate aspects of data governance that are rarely documented, much less presented. Additional takeaways focus on:
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 35 years, Peter has learned from working with hundreds of data management practices in more than 30 countries, including some of the world's most important. Among his 12 books are the firsts: 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 from Dataversity.net. Starting before Google, before data was big, and before data science, Peter has founded several companies that have helped more than 200 organizations leverage data–specific savings have been measured at more than $1.5B USD. His latest is Anything Awesome.