Data Modeling for AI

Presented by Dave Wells

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. 

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