Field reference
How to get the complete, authoritative column list for each dataset.
The Datasets pages document the columns an extract actually uses, plus the traps. Reading the columns maps them into families; Column values lists what the status columns can contain. They are deliberately curated: Tickets alone has 342 columns, and a 342-row table is not documentation anybody reads.
For the complete catalogue, ask the service — it is generated from the running build and can never be out of date.
$metadata — the authoritative source
GET https://<your-api-host>/api/ticketinghub/odata/v1/$metadata
Returns the CSDL document describing all four datasets: every column with its type and nullability, the key columns, and an Org.OData.Core.V1.Description annotation per column holding its business label.
This is what most BI and ETL tools read to map the schema for you, and what you should point a code generator at.
$metadatadescribes types, not value sets. A status column appears there asEdm.String; what it can actually contain is in Column values.
OpenAPI
GET https://<your-api-host>/api/ticketinghub/swagger/v1/swagger.json
Carries the same labels as OpenAPI property descriptions, alongside the four routes and their query options. Convenient if your tooling speaks OpenAPI; $metadata is the richer of the two, because it also states keys and nullability.
Which to use when
| You want | Use |
|---|---|
| A BI or ETL tool to map the schema | $metadata |
| Keys, nullability, exact types | $metadata |
| An OpenAPI document for code generation | swagger.json |
| To find a column among 342 | Reading the columns |
| To know what a status column can contain | Column values |
| To know what a column means in practice | the Datasets pages |
| To know what a term means | Glossary |
| To know what will silently give a wrong number | Getting the numbers right |