Prerequisite: None
This session will include a moderated Q&A featuring questions from the live audience.
It is well understood that advanced analytical modeling can benefit from well-governed, high-quality data in producing trustworthy outcomes. Although there are some nuances in how governed data sets are leveraged and interpreted during analytical modeling, what about the data that the analytical model creates? If we consult traditional data governance methods, who is the data owner and who is the data steward?
The data created during the advanced analytical modeling process introduces new challenges to our traditional data governance model. It is essential that organizations address these challenges in order to define accountabilities and increase trust in modeling recommendations.
In this session, Richard Hines will explain modern data governance techniques and best practices that you can apply to your analytical modeling process. These techniques enable your teams to ensure that advanced analytical results are trusted and acted upon.