Walk me through the SQL you would write and the insights you would derive from the results, including how you would visualize them.
Use the tables in the schema to produce a concise performance view by listing and month. Keep the answer focused on the result set and the analysis you would present.
listing_id, month, views, bookings, booking_rate.listing_id, then month ascending.| Column | Type | Description |
|---|---|---|
| listing_idPK | INT | Unique listing identifier |
| listing_name | VARCHAR(100) | Listing name |
| city | VARCHAR(50) | Listing city |
| is_active | BOOLEAN | Whether the listing is active |
| Column | Type | Description |
|---|---|---|
| metric_idPK | INT | Primary key for the daily metric row |
| listing_id | INT | Listing identifier |
| event_date | DATE | Date of the metric |
| views | INT | Number of listing views on the date |
| bookings | INT | Number of bookings on the date |