Field note · May 29, 2025
Five minutes with opened_at in support-tickets
4,000 rows, 3,990 distinct values, and the one fact about opened_at that changes how you query it.
Someone asked what is in opened_at on support-tickets, and the honest answer took one query.
4,000 rows, no nulls, 3,990 distinct values. When the ticket arrived.
It runs from 2023-01-01 02:15:00 to 2024-02-04 17:27:00, covering 400 distinct days.
It is a timestamp, not a date, which means every comparison against a bare date is a comparison against midnight. opened_at <= date '2023-06-30' silently excludes almost all of 30 June. Half-open ranges — >= start and < end — avoid the whole class of off-by-one-day bugs and read no worse.
select
count(*) as rows,
count(opened_at) as present,
count(*) - count(opened_at) as nulls,
count(distinct opened_at) as distinct_values
from support_tickets;Check the range before filtering on it. Half the "the dashboard is empty" reports we have seen are a date filter outside the data's actual range, and the query is not wrong so nothing errors.
Where this bites: 400 populated days is what any window function over this column has to work with. A seven-day lag counts rows, not days — so if a day is missing, lag(7) quietly compares against eight days ago and the week-over-week number is wrong in a way that looks plausible.
The grain is one row per ticket, which is the context every one of those numbers depends on. None of them survive a change of grain, which is why "profile the column" and "profile the table" are the same job. Full schema, and the CSV, on the dataset page.