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Fictional demonstration project.
A practical Excel data-cleaning workflow for turning a messy product list into a consistent, review-ready catalog.
This sample demonstrates how I can:
standardize SKUs and product names
normalize categories and status values
clean inconsistent spacing and capitalization
standardize numeric and price formats
identify and remove exact duplicates
preserve ambiguous values for review rather than guessing
maintain a clear change log of the cleanup performed
The project uses synthetic data only and was created as a portfolio demonstration.
Best suited for small product catalogs, supplier lists, inventory exports, ecommerce data and spreadsheet cleanup tasks where traceability matters.
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A client needed their books cleaned up from the company's inception and monthly financial reports for the current year.
Very insightful. Please Analyse it with Excell pvot table and so on..good luck
Messy books in. Clean books out. 📊
This is a simple before/after of a bank reconciliation (sample figures, no client data). Before: a duplicate payment and a missing entry left the books out by KES 13,650. After: both fixed, and the difference is KES 0.00.
This is the kind of work I do for small businesses every month:
✅ Bank and account reconciliations
✅ Accounts payable and receivable
✅ Invoice and payment processing
✅ Month-end support and financial reporting
This is a great example of how proper bookkeeping makes a real difference! Clean reconciliations lead to more accurate records and better financial decisions. 👏📊
Inventory data cleanup — self-initiated Excel demo using synthetic data. AI-assisted, not a client engagement. The example tracks original rows, inconsistent SKU/category/price formats and duplicate copies. Missing values are flagged rather than invented. The image shows the synthetic source and duplicate-removal trace. Existing workbook and before/after demonstration: https://www.truelancer.com/portfolio/excel-data-cleaning-inventory-before-and-after-demo-335964
