Finance wants to flag high-value orders relative to each customer's own spending patterns. Using the orders table, find every order whose amount is strictly above that customer's average order amount — return id, customer_id, amount, and created_at, ordered by customer_id then amount descending.
orders
| column | type |
|---|---|
| id | INTEGER |
| customer_id | INTEGER |
| amount | NUMERIC |
| created_at | DATE |
| id | customer_id | amount | created_at |
|---|---|---|---|
| 1 | 1 | 50.00 | 2024-01-01 |
| 2 | 1 | 150.00 | 2024-01-15 |
| 3 | 1 | 100.00 | 2024-02-01 |
| 4 | 2 | 200.00 | 2024-01-10 |
| 5 | 2 | 400.00 | 2024-02-20 |
Customer 1 avg = 100. Orders above: id 2 (150). Customer 2 avg = 300. Orders above: id 5 (400).
| id | customer_id | amount | created_at |
|---|---|---|---|
| 2 | 1 | 150.00 | 2024-01-15 |
| 5 | 2 | 400.00 | 2024-02-20 |