
E-Commerce Data Cleaning & Analysisis - SQL Portfolio Project
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€350(approx. $403)
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Full-Stack Web & Mobile App Developer With AI Integration & Automation Expertise
Certified Website Designer/Developer ➡️ WORDPRESS ➡️ WIX ➡️ WIX WEBSITE REDESIGN ➡️ WIX WEBSITE DESIGN ➡️ SQUARESPACE

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Full-Stack | Headless WordPress | Shopify | AI Integration Specialist | WooCommerce | Bug Fix & Performance Optimisation | 90+ Projects

UI/UX Expert | Graphic Design | Logo Branding |Fullstack Developer & SEO Expert| Custom Branding | Laravel | Shopify | WordPress
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Description
Experience Level: Intermediate
Estimated project duration: less than 1 week
I'm looking for a skilled Data Analyst to review my e-commerce data analysis portfolio project and provide feedback OR hire me for similar work.
PROJECT DETAILS:
- Dataset: 541,909 online retail transactions (2010-2011)
- Tools used: SQLite, DBeaver
- Tasks performed:
✓ Data cleaning (nulls, duplicates, zero values)
✓ Date format standardization (MM/DD/YYYY → ISO format)
✓ Customer segmentation (created SalesChannel column)
✓ Revenue analysis by product and country
✓ Missing data analysis (24.93% missing CustomerID)
KEY FINDINGS:
- Top 2 products contributed > $370,000 revenue
- 75% transactions from registered customers ($8.3M)
- 24.8% anonymous transactions ($1.44M) - opportunity for data capture
- Hong Kong identified as RetailStore (100% missing CustomerID)
**WHAT I NEED:**
- Review of my SQL queries and methodology
- Feedback on data cleaning approach
- Suggestions for improvement
- OR hire me for similar data analysis projects
DELIVERABLES:
- Cleaned dataset ready for visualization
- SQL scripts with documentation
- Summary of insights and recommendations
Budget: Open to discussion based on project scope
PROJECT DETAILS:
- Dataset: 541,909 online retail transactions (2010-2011)
- Tools used: SQLite, DBeaver
- Tasks performed:
✓ Data cleaning (nulls, duplicates, zero values)
✓ Date format standardization (MM/DD/YYYY → ISO format)
✓ Customer segmentation (created SalesChannel column)
✓ Revenue analysis by product and country
✓ Missing data analysis (24.93% missing CustomerID)
KEY FINDINGS:
- Top 2 products contributed > $370,000 revenue
- 75% transactions from registered customers ($8.3M)
- 24.8% anonymous transactions ($1.44M) - opportunity for data capture
- Hong Kong identified as RetailStore (100% missing CustomerID)
**WHAT I NEED:**
- Review of my SQL queries and methodology
- Feedback on data cleaning approach
- Suggestions for improvement
- OR hire me for similar data analysis projects
DELIVERABLES:
- Cleaned dataset ready for visualization
- SQL scripts with documentation
- Summary of insights and recommendations
Budget: Open to discussion based on project scope
Johnny S.
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18 Mar 2026
Indonesia
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Hi Johnny, could you confirm whether you want feedback only on the SQL and cleaning methodology, or whether you’d also like annotated improvements / corrected queries as part of the review?
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