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The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Supply Chain Data Cleaning - Supplier Inventory Fix
Project: Cleaned messy supplier file with 532 rows for a small business.
BEFORE: Data had duplicates, inconsistent names (safaricom LTD vs SAFARICOM LTD), missing quantities, NULL prices, extra spaces.
WHAT I DID:
✓ Removed 47 duplicate rows using Remove Duplicates
✓ Standardized 112 supplier names with TRIM & PROPER
✓ Fixed stock quantities: blank -> 0, "10 pcs" -> 10
✓ Cleaned price column: NULL removed, spaces trimmed
✓ Used VLOOKUP to add product categories
AFTER: 99.2% clean, ready for PivotTable reporting.
RESULT: Client saved 6 hours, now has accurate stock levels for reordering.
Tools: Excel, Google Sheets, VLOOKUP, PivotTable, Data Validation
Timeline: 24 hours delivery
Welcome! Are you looking to turn messy data into clear, actionable insights? You're in the right place.
As a professional data analyst, I specialize in transforming raw data into clean, structured, and visually compelling dashboards that help businesses make smarter decisions.
What I Offer:
• Data Cleaning & Preparation (Handling missing values, removing duplicates, formatting)
• Exploratory Data Analysis (EDA) to find key trends and patterns
• Interactive Dashboards & Reports (Power BI/ Excel)
• Custom DAX / SQL queries for deep metric tracking
• Professional summary report with key business insights
Tools I Use:
• Power BI
• Python & SQL
• Advanced Excel & Google Sheets
Why Choose Me?
• High-quality, clean design with user-friendly layouts
• Fast turnaround time and clear communication
• 100% satisfaction guarantee
Let's unlock the story behind your data! Please contact me before placing an order so we can discuss your specific project goals.
Zepto Sales Data Cleaning & Analysis
Processed and transformed raw Zepto sales data into a clean and well-organized Excel dataset. The project focused on correcting inconsistencies, formatting data, and preparing it for accurate analysis.
Excel features used: Text to Columns, Replace, UPPER/LOWER/PROPER, Paste Special, IF Function, and Pivot Tables.
The cleaned data was then analyzed to identify brand-wise loss insights, turning unstructured sales records into clear and useful business information.
