Data Dictionary Builder
Column names alone rarely explain units, business meaning or ownership. This builder keeps the current schema separate from its field definitions so additions and removals reveal where documentation has fallen behind. Edit meanings, types, units, allowed values, owners and required-value notes, then export readable HTML or a CSV reference.
Key features
- Build the current schema manually or from CSV headers
- Edit field meaning, type, unit, allowed values, owner and required status
- Find new undocumented fields and orphan definitions after schema edits
- Identify missing descriptions, types and owners separately
- Export static HTML and formula-protected CSV
- Save and restore a version 1 JSON project with raw strings intact
How to use
- Enter current field names, one per line, or import CSV headers.
- Create editors for undocumented fields and enter descriptions, types and owners.
- Optionally document units, allowed values and required status.
- Run the gap check and review new fields, orphans and incomplete entries.
- Save HTML or CSV and download project JSON to continue editing later.
Use cases
- Prepare field meanings and team ownership for a project handover
- Check documentation gaps after an export schema changes
- Record currency or measurement units for similarly named fields
- Share a static reference of allowed processing status codes
Frequently asked questions
How does this differ from a Markdown table generator?
It manages the relationship between a current schema and named field definitions, rather than only formatting a table. It detects undocumented columns and orphan definitions after additions or removals and retains those statuses in exports.
Does deleting or renaming a column erase its definition?
No. A new name is marked undocumented and the old definition becomes an orphan. Review it before removing it, or align the names in a saved project JSON file.
What makes a definition complete?
A current field is complete when it has a description, a specified type and an owner. Unit and allowed values are optional; required status is a documentation attribute. The tool does not validate the values of source records.
Can allowed values include commas or empty strings?
Yes. They are a JSON string array. ["A,B",""] preserves a comma-containing value and an empty string as separate values. [] means the document does not restrict allowed values.
Why provide HTML, CSV and project JSON?
HTML is a readable or printable static document, and CSV is a tabular reference. JSON preserves the title, schema and raw definitions for editing in this tool later. Incomplete entries are exported with their statuses.
Will my work remain when I revisit the page?
No automatic storage is used. Download project JSON before leaving and import it next time. Projects support up to 256 KiB, 32 schema columns and 64 definitions including orphans.
Privacy
Schemas, definitions and selected files are processed in current-page memory. This tool does not send input to servers, URLs, analytics events or browser storage, and does not save automatically. Imported CSV data rows are discarded after headers are extracted. HTML, CSV and project JSON files are created only when you request a download; clearing or leaving the page discards in-memory work.
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