I will clean the duplicate data from your spreadsheet
Spreadsheet Cleanup Specialist
About this Gig
Excel's built-in "Remove Duplicates" only catches duplicates where the entire row matches character for character. It won't find duplicates if your list has values with:
- Different formats
- Extra spaces between before or after words
- A unique column like Id or Created Date
I'll ask a couple questions to understand your data, then merge duplicates on your specifications and standardize formats. I'll sent back a clean spreadsheet and a list of everything removed.
With the higher tier packages, I'll find suspected duplicates based on things like:
- Nicknames
- Abbreviations
- Common typos
Excel and CSV both supported. Output matches your input format. File metadata preserved.
Your file is processed for your order and deleted after delivery for privacy and security
FAQ
What is meant by "100 Items Cleaned"?
You can ignore that. It's something that Fiverr puts there automatically for this type of job. The only limits are the total number of rows in the tier descriptions.
What kind of duplicates does this catch that Excel's built-in feature doesn't?
Excel's "Remove Duplicates" requires character-for-character matches across the entire row. If your data has formatting differences in phone numbers, mixed-case emails, trailing spaces, or extra metadata columns (Created Date, Row ID) that distinguish otherwise-identical rows, Excel keeps both.
Do you accept CSV files as well as Excel?
Yes, xlsx and csv are both supported. The output matches the format you sent: Excel in, Excel out (single file with multiple tabs); csv in, csv out (separate files for the cleaned data and the removed rows, zipped together)
How large a file can you handle?
Basic handles up to 10,000 rows. Advanced handles up to 50,000 rows. Premium handles up to 100,000 rows.
Can you find duplicates that aren't quite identical?
Yes, that's done for both the Advanced and Premium tier. "Bob Smith" will be considered a suspected match of "Robert Smith", bsmith@gmail.com will be considered a suspected match of bsmith@gamil.com, etc.
What's in the Premium tier's data quality report?
A written summary covering the duplicate patterns I observed in your file (for example, what percentage came from phone-format variations versus mixed-case emails versus metadata-column noise), and specific recommendations to prevent future duplicates.
What if I'm not satisfied with the result?
Message me and I'll make it right.
