What Is a Data Dictionary? Why AI Buyers Ask for One Before a Licensing Deal
By Andrew Smart, founder of MON$TER · About
A data dictionary is a plain document that explains every field in a dataset: its name, what it means, what kind of value it holds and where it comes from. Think of it as the legend on a map. Without one, a buyer sees columns of numbers and codes. With one, they can tell in minutes whether your data fits what they're building.
What goes in a data dictionary
- Field name — exactly as it appears in your system
- Plain meaning — "date the order shipped," not just "ship_dt"
- Type and format — date, number, text, yes/no, currency
- Allowed values — what each code or status means
- Source — which software or process creates it
- Coverage — the date range and how often it updates
- Privacy note — whether the field was removed, masked or aggregated
Why AI buyers ask for it
Buyers can't judge value from a file name. A data dictionary lets them check fit, quality and history without seeing your raw data, which keeps you safer early in the process. It usually sits next to the dataset description in the data room, and it shows which personal fields were taken out (see what counts as PII). A clear, complete dictionary also makes your data easier to value and can speed up review.
How to build a simple one
Export the column list from each system, then add one plain-English line per field. A spreadsheet works fine. Ask the person who knows the software best to fill gaps, and mark anything that holds personal information so it can come out before licensing. It doesn't need to be fancy, just accurate and complete.
More terms in the glossary, and the full process in how to license your data step by step. Curious what your data could be worth? Start at Business Data.