Incremental models in DBT optimize data processing by allowing updates to large tables without full refreshes. This lesson covers the key strategies for implementing incremental models, including append, merge, delete plus insert, and micro-batch techniques, which are essential for data engineers working with extensive datasets. Participants will learn how to configure these strategies effectively in their DBT projects, enhancing performance and efficiency in data workflows.