SharePoint Excel ingestion, Dataflow Gen2 vs shortcut + notebook CU efficiency

Hi bj132175​ , 

yes, Lakehouse shortcut + notebook (PySpark) is generally the more Capacity Unit-efficient approach. Multiple benchmarks show Dataflow Gen2 consistently consumes significantly more CU than code-first approaches like notebooks, in some tests, 55% to 700% more depending on data volume and transformation complexity, since Gen2 bills across Mashup, SQL, and FastCopy engines simultaneously rather than a single execution engine. For SharePoint Excel-folder ingestion specifically, shortcut + notebook avoids the Dataflow Gen2 overhead entirely and gives you more control over transformation logic, at the cost of needing PySpark skills on your team instead of a no-code interface. If your files/transformations are relatively lightweight, this gap may matter less, but at scale the notebook approach is the more CU-efficient recommended pattern.