A caveat first, most of the data I work with is under 10k rows. YMMV.

I find Excel slower than Python for analysis but I share a lot of data modelling with non technical people, and we both like being able to verify the results with pivot tables and functions typically (I need my work to be easily “defensible” because often facts are different from someones “feelings”). So workflow has become something like:

plan -> code -> generate outputs -> generate an XLSX -> verify with pivots/functions ->share with stakeholders

Python pipeline does the transformation and modelling, excel is review/verification, sharing layer.

The (sorta) issue is that the workbook becomes an output, not a source of truth.

People can add pivots and review tabs, but I ask that they provide corrections/feedback outside of generated sheets (otherwise those changes will disappear the next time I run the pipeline and recreate the workbook).