Power Users in March

Find users who logged in on at least 8 distinct days in March 2026.

Expected output

user_id, active_days. Sorted by active_days descending, then user_id.

Row order is checked. Column names are not checked; numbers are compared to 2 decimals.

Dataset: B2B SaaS product events

A project-management SaaS: company accounts, their users, product event logs (Jan to Apr 2026) and subscription history.

accounts

One row per customer company.

users

One row per user. Every user belongs to one account.

user_id	INTEGER	primary key
account_id	INTEGER
signup_date	TEXT	YYYY-MM-DD, same day as the user's signup event
acquisition_channel	TEXT	organic, paid_search, referral or partner
country	TEXT

events

Product event log. Data ends on 2026-04-30.

event_id	INTEGER	primary key, increases with event_time
user_id	INTEGER
event_name	TEXT	signup, login, view_dashboard, export_report, create_project, invite_teammate, upgrade_click
event_time	TEXT	YYYY-MM-DD HH:MM:SS (UTC)

subscriptions

Paid subscription periods per account. An account with no rows is on the free plan.

subscription_id	INTEGER	primary key
account_id	INTEGER
plan	TEXT	team or business
mrr	REAL	monthly recurring revenue in USD
started_at	TEXT	YYYY-MM-DD, inclusive
ended_at	TEXT	YYYY-MM-DD, exclusive; NULL while active. May be in the future for a scheduled cancellation.

Engine: SQLite. Dates are text (YYYY-MM-DD); use strftime(), date() and julianday() for date math.