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How ticketing data works
Our domain, explained from the ground up. If you have not worked with trade-fair or event ticketing data before, this chapter is the difference between a model that works and one that quietly counts the wrong things.
Read the three pages in order, then keep the Glossary open while you build.
The short version: a fair event sells articles; a purchase is a sale; each sale produces tickets; each ticket belongs to a ticket owner who may not be the buyer; and each time someone walks through a door, the ticket produces a usage.
Subsections#sub
The chain: from fair to scanFive concepts, in the order they happen. Almost every column in the data hangs off one of them.People: buyer, holder, exhibitorWho is who. Getting this wrong is the most common cause of numbers that are subtly and confidently incorrect.Counting visitorsHow attendance is counted, and where the numbers actually come from.GlossaryTerms you will meet in the data and in this documentation, in plain language.