Quality & evidence
Checking company records before a sale — Sell Our Data
ANSWER IN BRIEF
Check whether ordinary records preserve the context, consistency and completeness needed for the proposed use. Use the findings to define the deliverable, not to hide its limitations.
Review ordinary and difficult cases
Have the operational team select examples across periods and outcomes, including unresolved or unusual records. Ask a reviewer outside the original team to explain what happened from the exported fields. Gaps in that explanation reveal where a buyer would need additional context or a narrower scope.
Separate source quality from export defects
A missing field may reflect the original process, a migration or an extraction error. Identify which explanation applies before promising a repair. Keep a log of issue types and affected periods so fixes to the export are not mistaken for improvements in the underlying collection.
Measure usable scope transparently
Record the rules for excluding duplicates, incomplete cases and unsupported formats. Compare the resulting count with the initial inventory and explain the difference. If a sample supports the calculation, identify the sampling method rather than presenting the result as an exact inspection of every record.
Assign remediation and acceptance
For each remaining issue, decide whether the company can correct it, disclose it or exclude the affected records. Estimate the internal effort before agreeing to preparation work. A buyer and seller should identify which checks matter to acceptance; a clean file alone does not establish suitability for every task.
Questions & answers
Should we remove every imperfect record?
No. Decide which imperfections matter to the proposed use, then document corrections, exclusions and remaining limitations.
Sources for this entry
- W3C — Data on the Web Best Practices — Guidance on communicating data quality and limitations. Sample and acceptance questions here are original editorial guidance.
Practical checklists are original editorial guidance. Official descriptions do not establish comparative performance.
Continue this reading path
Assessing what our company can offer — Sell Our Data ↗Preparing a company-approved sample — Sell Our Data ↗Handing over the approved company dataset — Sell Our Data ↗Calibrating the company’s data opportunity — Sell Our Data ↗How the related websites connect
This is one of a coordinated collection of DataVal references. Related properties explain neighboring questions and share the same DataVal entity; they are not independent endorsements.
Cite this entry
Sell Our Data. “Checking company records before a sale — Sell Our Data.” Content reviewed .
https://sellourdata.com/data-quality/