Glossaries

Business glossaries overview

A glossary is where your organization writes down what its business words mean. Each glossary holds terms — “Customer”, “Net Revenue”, “Active Subscriber” — and each term carries an agreed definition, the people who own it, the other words people use for it, and links to the tables and columns where it lives in your data.

When a new analyst asks “what counts as an active customer?”, the glossary is the answer they should find.

In the app: Business Context › Glossaries

[screenshot]
The Glossaries page in Glossaries view, with two glossaries expanded to show their term trees and status badges.

Why it matters

Schemas describe data technically: a column is cust_status, varchar(20), not null. They don’t tell you what “status” means to the finance team. A glossary closes that gap.

  • One definition per concept. Term names are unique across your whole organization, so there is only ever one “Customer” to point to.
  • Clear ownership. Every term can name owners and subject-matter experts, so readers know who to ask.
  • A bridge to the data. Terms link to tables, columns, views, procedures, and functions in your schemas.
  • Context for AI. Glossary terms are one of the sources the ontology generator can read when it drafts an ontology for you.

What a term carries

Part What it holds
Name The display name. Unique across every glossary in your organization.
Status Draft, In Review, Certified, Contested, or Deprecated.
Definition The agreed meaning, in plain text.
Current usage & examples How people use the term in practice.
Parent term Places the term under another term in the same glossary, so glossaries read as a tree.
Synonyms Other terms that mean the same thing.
Acronyms Short forms such as MRR or NPS.
Related terms Terms connected in some other way, with a note that says how.
Related entities Tables, columns, views, procedures, and functions in your schemas.
Owners and experts Team members accountable for the term, and people who know it well.
Links URLs to wikis, policies, or runbooks.
Custom attributes Your own structured fields, such as a data classification or a review date.

How glossaries fit with the rest of Kenseme

  • Schemas say how data is stored. Glossary terms say what it means. Link the two with related entities.
  • Custom attributes add typed fields to terms. See Attributes vs labels vs glossary terms for when to use which.
  • Processes hold longer documents. The Glossary Extractor can read a process document and suggest terms from it.
  • Ontologies model the business formally. The ontology generator can use your glossary terms as a source.

Browse your glossaries

The Glossaries page has two views. Switch between them with the selector in the page header.

  • Glossaries shows one collapsible card per glossary, with its term count and its terms laid out as a tree. Every card starts collapsed.
  • List shows every term in the organization in one table, with its glossary and status. Use Search terms... to filter by term name, definition, or glossary title, and the All statuses dropdown to show only one status.

The header also shows how many terms you have across how many glossaries. The view you pick is kept in the page address, so a bookmark or the browser’s back button returns you to the same view.

Note: When your organization is in read-only mode, you can still browse every glossary and term, but the add, edit, import, export, and delete buttons are disabled. See Account states and read-only mode.

Where to start

  1. Create a glossary for one business domain.
  2. Add terms by hand with Define a term, or let the Glossary Extractor suggest them from a document.
  3. Relate terms to other terms and link them to schema objects.
  4. Bring in an existing glossary from a spreadsheet with Import and export a glossary.

Tip: Start small. Ten Certified terms that everyone agrees on are worth more than two hundred Draft ones nobody trusts.