A safer Excel and CSV cleanup workflow: blanks, duplicates, encoding and dates

Data cleanup becomes risky when deletion begins before the structure is understood. A safer workflow keeps the original file, makes changes in a predictable order and records what was removed. This matters for inventory, SKU lists, shipping records, contact lists and barcode source data.

Always preserve the original export

Do not clean the only copy of a file. Save a working copy and keep the original CSV or workbook unchanged. If Excel automatically changes an identifier or date, the original export is the reference you need to recover the intended value.

Clean structure before content

A practical sequence is: confirm column names, remove fully blank rows, trim unnecessary spaces, inspect data types, identify duplicates, normalize dates and numbers, then apply formulas or sorting. Building formulas on inconsistent data can make small errors harder to detect.

Define what “duplicate” means

Two identical rows are not the same as two rows sharing the same SKU. A SKU may legitimately appear with different batches, expiry dates or locations. Before deduplication, decide which fields form a unique record and preview how many rows will be affected.

Three common CSV traps

• Encoding: Chinese or other non-ASCII text can become unreadable when the wrong encoding is used.
• Leading zeros: identifiers such as 00123 may become 123 if treated as numbers.
• Automatic date conversion: text that resembles a date can be reformatted unexpectedly.

SKUs, barcodes, phone numbers and other identifiers should often be handled as text even when they contain only digits.

Validate after cleanup

1. Compare row counts before and after processing.
2. Record how many blank and duplicate rows were removed.
3. Spot-check the beginning, middle and end of the dataset.
4. Verify leading zeros in critical identifiers.
5. Test a small import before sending cleaned data back into another system.

WUCJ Excel Tools can speed up common conversions and cleanup tasks, but preserving the source file and validating the result remain essential when the data affects operations, stock or accounting.