Ask for a cleaning plan for a messy spreadsheet, not the cleaned data

An export from an old system comes out with "Sheffield", "sheffield " and "SHEFFLD" in the same column. Dates in two formats. A phone number that's lost its leading zero. A "N/A" in a column that otherwise holds numbers.

The obvious move is to paste the lot in and ask for a clean version. Don't. Past a few dozen rows it'll change things you didn't ask it to, and you won't be able to see which.

Ask for a diagnosis and a method instead.

Below are the column names and 30 sample rows from a spreadsheet export
(names and personal details replaced). Don't clean it. Tell me:
1. What's wrong with each column: inconsistent spellings or cases,
   stray spaces, mixed date formats, numbers stored as text, blanks that
   mean different things ("", "N/A", "-"), likely duplicates.
2. For each problem, how I'd fix it in [EXCEL / GOOGLE SHEETS / POWER QUERY],
   with the exact formula or steps.
3. What to check afterwards: row counts, totals, a count of unique values.
4. Anything where a person has to decide (for example two near-identical
   names that might be different people).
I'll run the fixes myself on a copy.

Columns and rows: [PASTE]

That gives you steps you can run on all fifty thousand rows and repeat next month on the new export. A one-off tidy by a chat tool can't do that.

Do it on a copy of the file and compare before and after: row counts, the total of the number columns, a count of unique customers or sites. If any of those moved and you didn't expect it, one of the steps did something you didn't mean.

Leave the near-duplicates to a person. "J Smith" and "John Smith" could be one person or two, and merging people on a guess is how records get corrupted.