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I took a raw customer orders sheet with extra spaces, mixed text cases, duplicate rows, five different date formats and inconsistent phone numbers. I cleaned it into a consistent table and flagged the missing values for follow-up instead of guessing. I used trim, proper, datevalue, substitute and Remove Duplicates.
#Excel #MicrosoftExcel #DataAnalysis #DataAnalytics #Spreadsheets #ExcelExpert #Freelance#DataCleaning #DataCleansing #DataPreparation #ExcelTips #DataQuality
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Most spreadsheet errors don’t come from bad formulas. They come from bad entries.
One person types “N/A”, another leaves the cell blank, a third writes “n/a “ with a trailing space. A date arrives as text. A region shows up as “North”, “north”, and “Norte”. Every formula downstream is correct, and the totals are still wrong.
Cleaning that up afterward works, but it’s the expensive way. It’s cheaper to stop the bad entry from getting in:
-- Use dropdown lists (Data Validation) for any field with a fixed set of values
-- Restrict date and number columns to valid formats
-- Add a short input message that explains what the cell expects
-- Keep a separate “lists” sheet so the allowed values live in one place
The goal isn’t to lock people out. It’s to make the right entry the easy one.
A spreadsheet that’s hard to fill in wrong rarely needs a cleanup project later.
Which field in your own reports causes the most cleanup work?
