Data validation for spreadsheets
A value can be neatly formatted and still be wrong. Data validation checks whether values make sense for the column they are in, so problems are found before they reach your analysis.
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What gets checked
Omixa looks for values that do not fit their column: words in a phone number column, ages below zero or above 120, an age of exactly zero (often a placeholder), negative quantities, and sign-up dates in the future. It also suggests likely misspellings, such as Lagoss for Lagos, without applying the correction.
These checks are plausibility warnings. A suspicious value is flagged for you, not changed, and the original is kept.
Setting your own standard with Quality Profiles
With Omixa Pro you can describe the standard a dataset must meet once, save it as a Quality Profile, and check any file against it. Each check returns a PASS, WARNING or FAIL result, with column-level quality scores for deeper analysis.
Validation is not correction
Consistent-looking data is not the same as correct data. When Omixa cannot tell whether a value is an error, it reports it and leaves the decision to you.
Steps
- Upload your file and open the findings.
- Review values flagged as invalid or suspicious.
- Accept, reject or keep each flagged value as it is.
- With Pro, save the standard as a Quality Profile and reuse it.
Common questions
What is a Quality Profile?
A saved description of the standard a dataset must meet. Pro users check files against it and get a PASS, WARNING or FAIL result.
Does validation change my data?
Flagged values are left as they were unless you choose a change.
Can I set my own rules?
Yes, with Omixa Pro, through Quality Profiles and per-column rules.
Related guides
- Data quality assessmentGet a data-quality score and report for a spreadsheet: what was found, what was fixed, and what still needs review. Practical, explainable, no guesswork.
- Handle missing valuesSpot blanks and placeholders like N/A, null and dashes, and decide whether to leave them or fill them. Omixa never fills gaps with estimates unless you ask.
- Standardize spreadsheet dataMake spreadsheet values consistent: dates, phone numbers, emails, countries, categories and capitalisation. Ambiguous values are flagged, not guessed.