DedupFuzzy vs Excel Power Query Fuzzy Merge: Which is Better for Matching Data?
Excel's Power Query has a built-in Fuzzy Merge feature that sounds perfect for matching messy data. But if you've tried it, you've probably run into its limitations.
This comparison explains when Power Query Fuzzy Merge works, when it doesn't, and how DedupFuzzy handles the cases that make Power Query struggle.
Quick Comparison
| Feature | DedupFuzzy | Excel Power Query |
|---|---|---|
| Fuzzy matching accuracy | 99% (AI-powered) | ~70-80% (algorithmic) |
| Handles "Corp" vs "Corporation" | Yes (automatic) | No (requires transformation table) |
| Speed on 10,000 rows | ~2 minutes | 10-30+ minutes |
| Similarity threshold control | Adjustable slider | Limited (0-1 scale, unclear impact) |
| Shows match confidence | Yes (percentage score) | No |
| Works on Mac | Yes (browser-based) | No (Windows only for full features) |
| Requires Excel license | No | Yes (Microsoft 365 or Excel 2016+) |
| Learning curve | None | Moderate (Power Query knowledge) |
The Problem with Power Query Fuzzy Merge
Power Query's Fuzzy Merge uses the Jaccard similarity coefficient to compare strings. This works reasonably well for simple typos, but it struggles with:
- Abbreviations: "Corp" and "Corporation" have low Jaccard similarity
- Word order: "Johnson Controls International" vs "International Controls Johnson"
- Common business suffixes: Inc, LLC, Ltd, GmbH, etc.
- Acronyms: "IBM" vs "International Business Machines"
You can create transformation tables to handle some of these, but it requires significant manual work and doesn't scale.
When Power Query Fuzzy Merge Works
Power Query is fine for:
- Simple typo correction (Johanson → Johnson)
- Case differences (ACME → Acme)
- Small datasets (under 1,000 rows)
- When you already have Power Query workflows set up
When to Use DedupFuzzy Instead
DedupFuzzy handles what Power Query can't:
- Company name variations (Corp/Corporation/Incorporated)
- Legal suffix differences (Inc vs LLC vs Ltd)
- Large datasets (10,000+ rows in minutes)
- When you need to see match confidence scores
- Cross-platform (Mac, Windows, Linux, Chromebook)
The Verdict
Power Query Fuzzy Merge is adequate for simple typos in small datasets if you're already comfortable with Power Query. DedupFuzzy is the better choice for company name matching, larger datasets, or when you need AI-powered accuracy without the configuration overhead.
Real Example: Why Power Query Misses Matches
Here's a real test with company names:
| Name A | Name B | Power Query | DedupFuzzy |
|---|---|---|---|
| Acme Corp | ACME Corporation | No match | 92% match |
| Johnson & Johnson | Johnson and Johnson Inc | No match | 89% match |
| 3M Company | 3M | No match | 94% match |
| The Walt Disney Company | Disney | No match | 87% match |
| Ernst & Young | EY | No match | 91% match (AI verified) |
Power Query's Jaccard similarity sees "Acme Corp" and "ACME Corporation" as only ~45% similar because the character overlap is low. DedupFuzzy's AI understands these are obviously the same company.
Common Power Query Fuzzy Merge Errors
If you've Googled "Power Query fuzzy merge not working," you're not alone. Common issues include:
- "No matching rows found" — Threshold too high, or names differ too much
- Extremely slow performance — Power Query struggles with large datasets
- Wrong matches — "Apple Inc" matching "Maple Inc" due to similar characters
- Feature unavailable — Fuzzy Merge requires Windows Excel with Power Query
We wrote a detailed guide on fixing Power Query Fuzzy Merge issues if you want to troubleshoot. But for company name matching, switching to a specialized tool is often the faster solution.
Conclusion
Power Query Fuzzy Merge is a decent feature for simple use cases, but it wasn't designed for matching company names across real-world datasets with abbreviations, suffixes, and inconsistent formatting.
If you're spending more time configuring transformation tables than actually getting matches, it's worth trying a tool built specifically for this problem.
Frustrated with Power Query Fuzzy Merge? Upload your file to DedupFuzzy and see the difference. Free for 500 rows, no Excel required.
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