CSV validation checklist

Define the CSV checks that protect your next import.

Turn reviewer knowledge into clear, repeatable checks that help partners correct issues early and give the receiving team a dependable CSV.

Readiness checklistSupplier price update CSV

StructureRequired columns and aliases reviewed

ValuesPrices, currencies, dates, duplicates

CorrectionSender guidance approved

Ready to put into practice

Complete checklist

Review the CSV from arrival through accepted handoff.

Review the applicable checks with the import owner using a representative partner file. The result becomes a shared standard DTO Flow can apply consistently to every submission.

1. Arrival and readability

Confirm that the expected file can enter the workflow safely and predictably.

The expected filename rule, extension, required status, deadline, and period are documented.
The file is non-empty, within the allowed size limit, and can be opened.
The character encoding, delimiter, quoting, decimal separator, and line endings are understood.
Unexpected duplicate files and permitted additional attachments have an agreed treatment.

2. Header and columns

Make structural drift visible before row values reach the import.

The header row is easy to identify and required columns have agreed standard names.
Approved partner-specific aliases are listed without hiding genuinely missing columns.
Unexpected columns, column-count changes, and reordered columns have a reviewed policy.
Each column has a defined type, format, required status, and sender-facing label.

3. Values and records

Define the repeatable checks that determine whether rows are usable.

Required cells, identifiers, dates, numbers, lengths, and formats are explicit.
Accepted values, reference values, minimums, maximums, and relevant patterns are reviewed.
Unique identifiers and duplicate business keys are checked at the correct scope.
Row-count limits and meaningful changes from earlier accepted files have safeguards.

4. Feedback and acceptance

Connect precise findings to partner correction, team approval, and the accepted handoff.

Every validation issue can be explained with file, row, column, expected value, and safe guidance.
The partner knows how to submit a corrected file for the same period.
The agreed checks are reviewed before launch and earlier results remain traceable when expectations change.
The receiving team knows which accepted original moves forward.

Completed example

Supplier price update readiness

A realistic review turns broad expectations into checks the sender can act on.

Selected checks for supplier_price_2026-08.csv
Checklist area	Reviewed expectation	DTO Flow outcome
Encoding	UTF-8, comma delimiter, quoted text allowed	The CSV opens consistently
Columns	Supplier ID, item ID, price, currency, effective date required	Required columns are recognized
Values	Positive price; EUR or USD; ISO date	Prices, currencies, and dates are checked
Duplicates	Supplier ID + item ID + effective date must be unique	Submission duplicate safeguard
Acceptance	All blocking checks pass before purchasing retrieval	One current accepted submission

How to use it

Turn a familiar CSV into an approved validation standard.

Focus on the conditions that make the file dependable for the receiving process.

Gather representative files
Review a usable file, common correction examples, and the import expectations the receiving team already applies.
Mark applicable checks
Agree which conditions block acceptance, which aliases are intentional, and what feedback helps the partner correct the file.
Configure and test
Bring the agreed checks into DTO Flow, test representative files, review the results, and approve them for future submissions.

Put the checklist to work

DTO Flow repeats the checks without repeating the manual review.

DTO Flow applies the agreed checks consistently and returns precise correction guidance through the same submission.

Arrival controls

Expected file, deadline, period, format, and matching stay attached to the feed.

Partner context

Each incoming feed keeps its partner, submission period, attempts, and status connected.

Exact findings

Agreed structure and value rules identify affected rows and columns before acceptance.

Accepted input

The receiving team works from one accepted file instead of choosing among copies.

Checklist questions

Choose checks that protect the real import.

Who should review the checklist?

Include the import owner, a data or IT owner who understands the file, and the operations person who coordinates corrections with the partner.

Does the checklist require an identical filename every period?

No. Document a matching rule that recognizes dated or period-specific exports while still connecting the upload to the intended expected file.

Should every listed check block acceptance?

Use the checks that define a usable input for your process. Keep blocking rules precise and give the sender correction guidance they can safely act on.

How does the reviewed checklist enter DTO Flow?

Bring the agreed columns, names, types, values, formats, and duplicate checks into DTO Flow, test representative files, and approve the results for future submissions.

Apply the reviewed checks

Give the next partner CSV a reusable validation workflow.

Start with the structure and values your receiving process already depends on.

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