A data engineering team uses a Dataflow Gen2 in Fabric to ingest a large sales transaction table into a lakehouse. The source table grows by roughly 500,000 rows daily, but historical rows are never modified. Each scheduled refresh currently reprocesses the entire table, causing long run times and high capacity consumption. The team wants to reduce refresh duration while keeping the destination data accurate. Which approach should they configure?