The original interview report identified a late-order SQL exercise but did not preserve its exact schema. The following is a self-contained practice reconstruction of that topic. You have a PostgreSQL table: ```text orders ------ order_id BIGINT PRIMARY KEY created_at TIMESTAMPTZ NOT NULL promised_delivery_at TIMESTAMPTZ NOT NULL delivered_at TIMESTAMPTZ NULL status TEXT NOT NULL -- 'completed', 'cancelled', or 'failed' delivery_zone TEXT NOT NULL -- non-empty delivery market zone ``` Write one PostgreSQL query that produces one row for every UTC calendar date and delivery zone that has at least one eligible order. An eligible order has `status = 'completed'` and a non-null `delivered_at`. Exclude completed rows whose `delivered_at` is null; exclude all cancelled and failed rows. The three grouping/comparison fields `created_at`, `promised_delivery_at`, and `delivery_zone` are guaranteed non-null, and `delivery_zone` is guaranteed non-empty, so no additional null or unknown-zone bucket is needed. Return these columns: - `order_date`: the UTC calendar date obtained from the instant in `created_at`, regardless of the timezone offset originally used to write that value - `delivery_zone` - `completed_orders`: number of eligible orders in the group - `late_orders`: number of eligible orders where `delivered_at > promised_delivery_at` - `late_order_rate`: `late_orders / completed_orders` as a decimal between 0 and 1 - `previous_date_late_order_rate`: the late-order rate for the preceding available `order_date` in the same zone, or `NULL` for the zone's first date - `late_order_rate_change`: current rate minus `previous_date_late_order_rate`, or `NULL` when there is no previous rate An order delivered exactly at its promised time is on time. Preserve full numeric precision; do not format the rates as strings or percentages. Order the final result by `order_date` ascending and `delivery_zone` ascending.