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While training with the finance team during Hajj season, I was asked to clean up a sales report that mixed company inventory with supplier-shared products, requiring accurate profit-sharing calculations. The original report relied entirely on manual calculations, so I rebuilt it using Excel functions to calculate Total Sales, Total Cost, and Net Profit.
This single change uncovered a 7,949 SAR discrepancy between the original and rebuilt figures. Tracing the gap, I found a combination of issues: manual calculation errors, missing selling prices on several items, cost and selling prices entered in swapped columns, and a missing zero in one of the recorded values. Correcting these gave the company an accurate Net Profit figure and ensured suppliers were paid the correct share of the proceeds.
Net Profit is blurred for confidentiality reasons. You can check the before and after report.
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I run a SaaS business. As founders we're often too immersed into our product and can overlook what real people need to hear. A few hurtful patterns that keep showing up in websites, and how to fix them:
Focusing on the features, not the value:
❌ “Automated bank reconciliation engine”
✅ “Close the books on the 2nd, not the 12th.”
Features matter to someone already comparing options. Everyone else needs to recognize their own problem first, then see it solved.
Big words that could belong to any company:
❌ “Seamless. Powerful. Built to scale.”
✅ “Payroll for 40 people in ten minutes, not an afternoon"
Unverifiable claims:
❌ “Trusted by leading clinics”
✅ “No-shows down 30% across 200 clinics”
What’s the vaguest headline spotted this week? Drop it below 👇
One I keep seeing on AI tools is "Supercharge your workflow with AI." It says nothing. Something like "Turn a 40 minute sales call into a follow up email in 2 minutes" does far more work. Your before and after examples make the point very clear.
Gen Z Career Aspirations – Data Cleaning
Cleaned and organized survey data as part of my Gen Z Career Aspirations Analytics project.
Key tasks performed:
Handled missing and inconsistent values
Standardized categories and text fields
Identified and handled duplicate records
Organized columns for further analysis
Created a structured dataset for EDA and dashboard development
Tools Used: Microsoft Excel, Power Query, Excel Formulas
This work helped prepare the survey dataset for accurate analysis and meaningful insights.
