Store delivery scorecard

You are a data analyst at a convenience store chain. The head of operations is preparing a weekly summary of online orders and wants a per-store picture: how many orders were placed in total, how many reached the customer, how many were cancelled, and how much revenue came from delivered orders only. The data lives in the orders table: one row per order, status is one of 'delivered', 'cancelled', 'returned', and the order amount is always present (never NULL). Conditional metrics are computed with conditional aggregation: a CASE expression inside an aggregate function. Return columns: - store — store name (text); - total_orders — total number of the store's orders (integer); - delivered_cnt — number of orders with status 'delivered' (integer); - cancelled_cnt — number of orders with status 'cancelled' (integer); - delivered_revenue — sum of amount over delivered orders only, rounded to 2 decimals; 0 if the store has no delivered orders. Sorting: by store ascending. Every store present in the table appears exactly once; the 'returned' status only contributes to total_orders.