Data modeling is an essential skill set for modern data management that has an important (but frequently unrecognized) role in artificial intelligence. Data modeling and AI are both evolving fields. Everyone is aware of AI evolution because it is at the forefront of technology news. It seems that evolution of data modeling is a well-kept secret. Data modeling of the past was aligned with design of relational databases. Today’s data modeling addresses many data types — relational, key-value, wide-column, document, graph, and more — at all levels from business semantics to design and implementation.  

AI models depend on data. Discriminative AI models classify existing data and use it to infer predictions and conclusions. Generative AI models create new data that is collected, stored, managed, and used as feedback. Modern data modeling provides the foundation to organize, understand, prepare, and manage data for AI. Data models provide business context, describe data content and organization, support feature engineering and data preparation, and reinforce model interpretability. Join this session to learn about the strong synergies of AI and data modeling. 

Speaker: Dave Wells 

Consultant and Educator, Infocentric 

Dave Wells is the Education Director for eLearningCurve as well as the author and instructor of several eLearningCurve courses. Dave works as an educator and consultant in the field of data and information management. He has more than 50 years of experience working with data and technology in many roles including application development, data architecture, data governance, IT management, business management, technology research, and more. Dave also has more than 30 years of experience as an information management and information technology educator including curriculum management, instructional design, course development, and teaching in live classroom, virtual, and e-learning formats. See Dave’s blog at eckerson.com to read his thoughts about a variety of data and information management topics.