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Moradeyo Maleek
Automating messy data cleaning with Excel & Power Query.
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GALLERY L
Ibadan, Nigeria
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Ibadan, Nigeria
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Shopify + Etsy + Ad Spend — Turning Raw Exports Into a Profitability Picture Client sold on Shopify and Etsy, ran ads on Facebook and Google, had no idea if she was profitable. 4 pages of raw, disconnected data came in. 2 days later: net revenue after returns, total ad spend across both platforms, and which products actually made money — 11 clean, connected pages. The hardest part wasn't the math — it was getting the data to agree with itself. Mixed date formats, ad platforms reporting on different schedules, No shared key between sales and ad spend. All of it had to be standardized before a single number could be trusted. I don't charge a fixed price — I work within the client's budget and what the project's actually worth.
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Client request: two platforms, one mess. A candle store owner needed her Shopify and Etsy order data combined into one sheet showing revenue, top products, and top customers — without digging through two exports every week. The real work here was appending, not merging — Shopify and Etsy data needed matching headers before they could be stacked cleanly into one table. From there: standardized dates, removed duplicates, filled missing statuses, and built an interactive view she can actually use. I don't charge for data cleaning. I charge for solving e-commerce problems using my time and experience, and I work within the client's budget.
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ShopZone UK — 5 Sheet Ecommerce Merge, Returns Analysis & Automated Dashboard A UK online store came to me with orders, returns, customer details, product inventory and delivery partner data all sitting in 5 completely separate sheets with no connection between them. Duplicate records throughout. Inconsistent status values and IDs across every sheet. Missing amounts on multiple orders. Returns data disconnected from the orders it belonged to. Cleaned all 5 sheets independently then merged everything into one master orders table. Calculated all missing total amounts, net revenue after returns, profit per order and discount values applied. Built a pivot view showing net revenue by product category per order status. Delivered an input sheet with dropdown validation for Order Status, Product, Delivery Partner and Discount Code. Summary dashboard shows total revenue, total returns, net revenue after returns, total profit, delivered versus cancelled breakdown and two charts — Revenue by Category and Orders by Delivery Partner — all updating automatically with one refresh.
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MedCore Clinical Services — 3 Sheet Merge, Billing Automation & Department Dashboard A US medical clinic came to me with patient visits, doctor records and billing data sitting in 3 completely separate sheets with no connection between them. Duplicate visit records throughout. Department names written inconsistently across every row. Dates in 3 different formats. Missing patient balances on multiple records. Payment status incomplete across the billing sheet. I cleaned all 3 sheets independently, merged everything into one master clinical table and calculated all missing patient balances automatically. Built a pivot view showing revenue breakdown by department per visit type. Delivered an input sheet with dropdown validation for Department, Visit Type, Insurance Type and Payment Status so new patient data is always entered correctly. Final summary dashboard shows total revenue, total outstanding balance, busiest department, most common diagnosis, total visits and paid versus pending breakdown — two charts included, all updating automatically with one refresh.
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