Short answer: Excel handles basic data quality checks well for small, infrequent, simple files. Sohovi is better when you need to check the same file structure repeatedly, when the data is messy (fuzzy duplicates, mixed formats, encoding issues), or when you need a quality report you can share. Most teams need both at different points — Excel for quick one-offs, a dedicated tool for systematic work.
What Excel Does Well (Be Honest About This)
Excel is a legitimate starting point for data quality work:
- COUNTBLANK / COUNTA — finding empty cells in a column
- COUNTIF + COUNTIFS — spotting duplicate values
- Data Validation — constraining what can be entered
- Conditional Formatting — highlighting cells that fail conditions
- VLOOKUP / MATCH — cross-referencing against allowed value lists
- Filter + Sort — visual inspection of value distributions
- Power Query — repeatable data transformation and combining sources
Sohovi automatically finds every duplicate in your dataset — including near-matches — and shows you exactly which rows are affected.
An experienced Excel user can build a surprisingly capable quality checklist on a small, predictable dataset.
The Six Limits Excel Hits on Real-World Data
1. Scale
Excel holds over a million rows, but manual formula-based quality checks become impractical well before that. At tens of thousands of rows, maintaining formulas is slower than the insight they provide, and recalculation time becomes painful.
2. Fuzzy Duplicates
Excel's Remove Duplicates is exact-match only. "Acme Corp" and "Acme Corporation" are two different records in Excel's view. "John Smith" and "Jon Smith" — two different people. Real customer lists are full of these variants, and Excel has no mechanism to find them.
3. Reproducibility Across Files
Excel quality checks live in formulas tied to column positions and sheet names. When a new file arrives with slightly different column names or order, the formulas break. You rebuild them by hand — every time.
4. Coverage Beyond What You Checked For
Excel checks what you told it to check. A purpose-built quality tool profiles the entire dataset automatically — including columns you weren't looking at — and surfaces problems you didn't anticipate.
5. Quality Scoring and Reporting
Excel doesn't produce a quality score you can share with a stakeholder or track over time. You see individual cell results, not an aggregate data quality picture. "Our contact list is 94% complete and has a 2.3% duplicate rate" is not something Excel gives you natively.
6. PII Detection
Excel has no concept of PII. It won't tell you that column F contains what looks like phone numbers, or that column H appears to be Social Security Numbers mixed with other content. For compliance-conscious teams, this is a meaningful gap.
The Same Task: Profiling a 5,000-Row Contact List
In Excel:
- Create a summary tab
- Write
=COUNTBLANK(Sheet1!A:A)/COUNTA(Sheet1!A:A)per column for null rates — repeat for every column - Write
=SUMPRODUCT(--(COUNTIF(Sheet1!B:B,Sheet1!B2:B5001)>1))/5000for duplicate rate - Create pivot tables for top values in categorical columns
- Build conditional formatting rules for outlier detection
- Time: 30–60 minutes on a familiar structure; longer if the structure changes
In Sohovi:
- Upload the file
- All columns profiled automatically: null rates, type distributions, top values, duplicate rate, outlier flagging
- Time: under 2 minutes
When Excel Is Still the Right Choice
Excel is still appropriate for:
- Quick one-off checks on small files (under 5,000 rows, one-time task)
- Data entry validation during manual data input
- Simple deduplication on clean, consistent data
- Ad-hoc lookups and cross-references against a reference table
The signal to move beyond Excel: you're spending more than 30 minutes per week rebuilding quality checks, you've caught errors only after they caused downstream problems, or different people are checking the same data differently (or not at all).
Frequently Asked Questions
Q: Does switching from Excel to a data quality tool mean giving up Excel entirely? No. Most teams use both: Excel for ad-hoc work and data manipulation, a dedicated tool for systematic quality assessment. They're complementary.
Q: What about Power Query — doesn't that solve the reproducibility problem? Power Query helps significantly. You can build a transformation that replays on new files. But it still requires manual setup for quality rules, doesn't handle fuzzy matching, and doesn't produce a quality score or sharable report. Power Query is Excel at its best for data work — and it still hits the limits above.
Q: Is Sohovi more expensive than Excel? Sohovi has a free tier. If you have Microsoft 365 for Excel, you're already paying for Excel. The comparison isn't "free vs paid" — it's whether the time your team saves on manual quality work is worth the tool cost. For most teams doing weekly quality checks, it is.
Q: Can Sohovi open Excel files directly? Yes — Sohovi accepts both CSV and Excel (.xlsx) files natively.
The Excel quality process you've built by hand is a set of documented quality standards — what fields must be complete, what formats are acceptable, what values are allowed. Those translate directly into Sohovi validation rules. Upload your file and see the same checks plus everything you weren't checking — automatically, in under a minute.