Lesson recap

In this lesson, you:

• Learned the benefits of partitioning your incremental models
• Added a time-based partition to an incremental model
• Created a second @dbt_assets definition specifically for incremental dbt models

The patterns you used are general enough that they can also be applied to any type of partition, allowing you to partition your incremental models by location, customer, or other dimensions. Tinker around with the context.partition_key property if you’re interested!

💡 Tip: Did you know dbt models can resolve schema changes on their own? Using on_schema_change: "sync_all_columns", you can avoid needing to fully refresh your dbt models and instead only orchestrate with Dagster backfills.