Tim Mitchell gives us the wherefore around incremental loads:
When moving data in an extraction, transformation, and loading (ETL) process, the most efficient design pattern is to touch only the data you must, copying just the data that was newly added or modified since the last load was run. This pattern of incremental loads usually presents the least amount of risk, takes less time to run, and preserves the historical accuracy of the data.
In this post, I’ll share what an incremental load is and why it is the ideal design for most ETL processes.
“Move less data rather than more data” is how I’d put it, but Tim does a much better job of putting it.