Field note · July 26, 2024

Five minutes with seats in saas-subscriptions

2,500 rows, 246 distinct values, and the one fact about seats that changes how you query it.

1 min read ·Data quality ·quality practice

Someone asked what is in seats on saas-subscriptions, and the honest answer took one query.

2,500 rows, no nulls, 246 distinct values. Seats at signup.

The five-number version: min 1, p10 1, median 8, p90 98, max 895. The mean is 51.

The p10 to p90 band — 1 to 98 — is where ordinary rows live, and it is the pair worth quoting when somebody asks what to expect. Min and max describe the two strangest rows in the table and nothing else; they are useful for spotting impossible values and misleading for everything else.

sql
select
  count(*)                as rows,
  count(seats)            as present,
  count(*) - count(seats) as nulls,
  count(distinct seats)   as distinct_values
from saas_subscriptions;

The mean sits 534% above the median, which is the whole story: anything that reports the average of seats is reporting a number most rows are below. Put the median next to it or drop the mean.

Where this bites: a filter like seats > 51 reads as "above average" and selects a minority of rows — a smaller minority than the phrase suggests to whoever asked for it. If the request was "the typical ones", the threshold they meant was 8.

The grain is one row per account, 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.