DataDoctor

Runs entirely in your browser — no uploads, no saved snippets, no public links.

Paste a file, inspect the issues, export reviewed output.

Schema compliance preflight

Schema Checker

Validate JSON or CSV data against JSON Schema and turn contract failures into readable fix steps.

Data mode

Paste data or load the matching sample.

Paste a JSON Schema contract for the selected data mode.

Next workflow

Continue the preflight

Generate JSON Schema

Infer a schema from sample JSON data.

Validate JSON Schema

Run the dedicated JSON schema validator.

Generate CSV Schema

Infer a schema from CSV columns and values.

After the tool runs

Schema Checker review guide

Use the tool above first. The supporting notes below help you interpret the result, fix the right issues in the right order, and choose the next DataDoctor tool without pushing SEO content above the actual task.

Best input

validating either JSON or CSV against one schema when you need a single contract check.

Output to keep

Keep the schema, sample data and validation report together so contract changes are traceable.

Next check

Refine required fields, enums and type rules, then validate a second sample before relying on the contract.

What it checks

Schema Checker for real data work

Schema Checker is for contract work: it checks whether the data shape matches the rules another system expects. Use it after the raw JSON or CSV parses cleanly.

  • JSON input mode
  • CSV input mode
  • Schema parsing
  • Readable contract failures

Fix these first

Common errors to review before downstream work

Most failures come from small file issues that become expensive only after an API call, import job or spreadsheet cleanup. Fix blocking errors first, then re-run the same tool before moving forward.

  • Schema syntax errors
  • Required fields absent from data
  • Wrong root type
  • CSV rows not matching object schema rules

Recommended workflow

Run the check in this order

When the report points to a path or row, fix the data when the source is wrong and fix the schema only when the contract was written too narrowly.

  1. Step 1

    Choose JSON or CSV input

  2. Step 2

    Paste the data and schema

  3. Step 3

    Run the schema check

  4. Step 4

    Fix the reported paths or rows and recheck

How to interpret a passing result

A pass means this specific preflight did not find the issues listed above. It is not a guarantee that the target system will accept every row, field, custom mapping or account-specific rule.

A generated or passing schema is not a final data contract until optional fields, nullable values and edge cases are reviewed.