Abdullah Qamar
Turning messy Excel data into clean, usable insights
New to Contra
Abdullah is ready for their next project!
📊 Completed: E-commerce Sales Data Cleaning & Reporting Project
I recently completed an Excel Data Cleaning project focused on preparing an e-commerce sales dataset for business reporting and analysis.
✔ Cleaned and standardized raw data
✔ Removed duplicate records
✔ Handled missing and inconsistent values
✔ Validated calculations and business data
✔ Created Pivot Tables for sales insights
✔ Organized the dataset for accurate reporting
I focus on delivering clean, reliable, and analysis-ready Excel data while preserving data integrity and documenting every important change.
🚀 I'm currently available for new freelance projects involving:
• Excel Data Cleaning
• Data Validation
• Spreadsheet Organization
• Pivot Tables & Pivot Charts
• Business Reporting
If you're looking for accurate and professional Excel data cleaning support, I'd be happy to help.
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Ecom data cleaning project
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Just wrapped up an exciting data cleaning project for an e-commerce . The client’s inventory software and shipping provider had a syncing error, leaving them with over 4,400 rows of absolute chaos.
The Challenges I Solved:
Duplicate Orders: Merged 306 duplicate split order IDs where names and emails were scattered across separate rows.
Corrupted SKUs: Standardized mixed-case and broken SKUs (like prod_789_m and PROD789M) into a uniform PROD-XXX-X format.
Dirty Phone Numbers: Cleaned up messy contact strings containing country codes, hyphens, and spaces into a crisp, 10-digit format for their shipping system.
Date Formatting: Resolved a critical mix of MM/DD/YYYY, DD-MM-YYYY, and raw Excel serial numbers.
The Result: Delivered a pristine, software-ready Master Sheet along with a detailed "Changes Log" tab.
📥 Need your messy Excel or CSV files cleaned before your next big analysis or system migration? Shoot me a DM or invite me to your project! #dataanalyst #datacleaning #excel #dataformatting #dataprocessing
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Inc companies 2019 data cleaned
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