Assume all timestamps are UTC. Treat "today" as 2025-09-01. Define "last 7 days" as the inclusive window [2025-08-26 00:00:00, 2025-09-01 23:59:59]. Schema (invented): users(user_id INT, signup_at TIMESTAMP, tz STRING) orders(order_id INT, user_id INT, order_ts TIMESTAMP, amount DECIMAL(10,2), status STRING) -- status in ('completed','canceled') events(event_id INT, user_id INT, event_ts TIMESTAMP, event_type STRING, product_id INT, device_id STRING) Sample rows: users user_id | signup_at | tz 1 | 2025-08-10 09:00:00 | America/Los_Angeles 2 | 2025-08-28 14:00:00 | UTC 3 | 2025-08-30 23:30:00 | America/New_York
orders order_id | user_id | order_ts | amount | status 101 | 1 | 2025-08-27 23:55:00| 20.00 | completed 102 | 1 | 2025-08-28 00:05:00| 15.00 | canceled 103 | 2 | 2025-08-31 12:00:00| 9.99 | completed 104 | 2 | 2025-09-01 00:00:10| 49.00 | completed 105 | 3 | 2025-08-26 23:59:59| 5.00 | completed
events event_id | user_id | event_ts | event_type | product_id | device_id 1 | 1 | 2025-08-27 23:50:00| view_product | 555 | A 2 | 1 | 2025-08-27 23:50:00| view_product | 555 | A -- duplicate of 1 3 | 1 | 2025-08-28 00:03:00| add_to_cart | 555 | A 4 | 1 | 2025-08-28 00:04:00| purchase | 555 | A 5 | 2 | 2025-08-31 11:58:00| view_product | 777 | B 6 | 3 | 2025-08-26 23:55:00| view_product | 999 | C 7 | 3 | 2025-08-26 23:58:00| purchase | 999 | C 8 | 2 | 2025-09-01 00:00:10| purchase | 777 | B Tasks (write a single Standard SQL query; CTEs allowed):