Get statistic groups

One row per article-to-statistics-group assignment. A small reference dataset that carries the many-to-many relation the ticket rows cannot express — and the place where audited attendance reporting is structured.

Load it whole — it is seven columns and typically a few hundred rows.

Grain and key

The complete dataset

All seven columns:

Why this is a separate dataset

An article is regularly a member of several statistics groups at once — a single column on the ticket row cannot represent that. Splitting it out is the only correct way to model it. In warehouse terms this is a bridge table, not a dimension.

Traps specific to this dataset

• The join multiplies rows. An article in three groups produces three rows per ticket. A COUNT(*) after joining counts assignments, not tickets — count distinct TicketInternalId.
• An article with no group has no row here. An inner join silently drops those tickets. Use a left join and decide explicitly what the unassigned bucket means — often it belongs in an "other" category rather than being dropped.
• IsFkmTotal and IsFkmVisitor are independent, not a partition. A visitor badge group is normally in both; a plain business category is a row with both false. Never derive one from the other, and never compute non-visitors as total minus visitor.
• No event context. Group membership is a property of the article, not of an event. The event comes from the ticket.

Joining

Join to Tickets on MandatorInternalId, ArticleInternalId. See How ticketing data works → Counting visitors for how to use the result correctly.

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Request

No request body.

• $select(string): rarely needed here — there are only seven columns.
• $filter(string): an OData predicate.
• $orderby(string): sort order.
• $top(integer): maximum rows, capped at 1000.
• $count(boolean): include the total count.
• $skiptoken(string): server-generated paging token.

Response

• @odata.context (string): the metadata URL describing this payload.
• value (array): the page of assignment rows.
• @odata.nextLink (string, optional): the next page; absent on the last one.
• @odata.count (integer, optional): present only when $count=true.

Three things to get right when you join

Join on MandatorInternalId and ArticleInternalId. Then:

The join multiplies rows. An article in three groups produces three rows per ticket. Count distinct TicketInternalId, never rows, or you will triple your attendance figure.

An article with no group has no row here. An inner join silently drops those tickets. Use a left join and decide deliberately what the unassigned bucket means in your report.

IsFkmTotal and IsFkmVisitor are independent flags, not a partition. Report them separately; never subtract one from the other.

See How ticketing data works → Counting visitors and the Audited attendance by statistics group entry in Recipes.