SAV Inspector Deutsch
HomeCheck a SAV file before it becomes someone else's problem.
SAV quality assurance

Check a SAV file before it becomes someone else's problem.

A file can open successfully and still be unsafe to hand over. Dictionary gaps, ambiguous missing codes, identifiers, broken references or an unverified rewrite may only become visible in the recipient's workflow.

Separate blockers, warnings and context

A useful quality check does not label every unusual property as an error. Blockers prevent a trustworthy output, warnings require attention and contextual findings may be acceptable when documented. Review notes should add audit context rather than hide a finding.

  • Duplicate or invalid variable names
  • Observed values without labels
  • Missing-value conventions
  • Constants and possible identifiers/open text
  • Weight and multiple-response references
  • Encoding and pending edits

Check the complete dataset

Quality scanning should not depend on the current UI filter. A rare unlabelled code or identifier may sit outside the visible rows. SAV Inspector's check evaluates the complete loaded dataset and links findings back to the relevant variable or editor.

Verify the file you actually deliver

After editing, write the complete SAV or ZSAV and immediately reopen it through the production reader. Compare cases, dictionary and supported file metadata, then record format, size, time and a SHA-256 hash where available.

This round-trip is evidence that the produced bytes can be read back consistently. It is not a promise that every proprietary extension is supported by every SPSS version.

Practical workflow
  1. Open the untouched source

    Record file properties and keep the original available for comparison.

  2. Run the complete check

    Review blockers first, then warnings and contextual findings.

  3. Resolve or document

    Follow findings to the affected variable and attach a concise review note when context matters.

  4. Round-trip the output

    Write, reopen, compare and retain the report and hash with the delivered file.

FAQ

Frequently asked questions

Does a successful open mean the SAV is correct?

No. It only shows that the reader can parse it. Dictionary quality, references, missing rules and handover fitness still require review.

Are identifiers always errors?

No. They may be required for joins, but they deserve explicit review because they affect confidentiality and downstream use.

What does a SHA-256 hash prove?

It identifies the exact file bytes and detects accidental changes. It does not prove that the contents are statistically or semantically correct.

Can the report contain the full data?

The quality report should focus on findings and metadata. Avoid copying sensitive case data into a broadly shared report.

SAV Workflow Check

Find out in 30 minutes whether SAV Inspector fits your workflow.

We take one concrete recurring SAV job, define the desired outcome and demonstrate the shortest Local or Teams path. No generic product presentation, no newsletter and no file upload by email.

  • one concrete workflow instead of a feature tour
  • no-upload Local demo or controlled Teams pilot
  • a shared success criterion
  • a clear recommendation — including when SAV Inspector is not a fit

Only used to reply personally to this request. No newsletter. No SAV file or file metadata is transferred through this form. Privacy Email us directly
Guides

Related guides

Inspect SPSS SAV files locally — without uploading them.Open and inspect SPSS .sav and .zsav files locally in your browser. Review variables, labels, missing values and cases without uploading the file.How to open a SAV file without SPSS.Open an SPSS .sav file without installing SPSS. Compare a local browser viewer, PSPP, R and Python, and choose the right method for your task.Know what is preserved before you open, edit or export.See which SPSS SAV and ZSAV metadata SAV Inspector reads, checks, edits and writes, plus the limits of local CSV and Excel imports.Edit a SAV file without losing track of the source.Edit SPSS variable labels, value labels, missing values and selected data without overwriting the source. Validate and write a new SAV or ZSAV file.