[elmolino89]

IMHO instead of ramming a square peg into a round hole one may think of switching from Excel to i.e. Jupyter notebook(s). Keep the raw data separate from the calculations/visualizations and get a more trackable environment.

You may also pinch out bunch of functions as separate scripts in a git repo and share these between various notebooks/people.

Calculate md5 checksums of raw data files. If values in rows can be modified, get the hash sums (xxhash?) per row. That way even with the lowest common denominator (text CSVs) you know if the inputs changed and where.

For larger data consider storing it in parquet format and using duckdb.

Assuming that you must have Excel output calculate what's needed using raw data, notebooks/scripts then output Excel using openpyxl