Food Delivery Dataset for SQL Database Analysis

• orders.customer_id →references customers.customer_idmany to one: each Orders row points to one Customers row
• deliveries.order_id →references orders.order_idmany to one: each Deliveries row points to one Orders row
• deliveries.driver_id →references drivers.driver_idmany to one: each Deliveries row points to one Drivers row

1. Calculate the average delivery time per region using orders and deliveries tables.

   You may need to calculate the difference between delivery_datetime and pickup_datetime to find delivery time.

   tables: orders, deliveries

2. Identify the top 5 customers by total order amount using customers and orders tables.

   Join customers and orders tables and group by customer to sum their order amounts.

   tables: customers, orders

3. Determine the busiest hours for order placement by analyzing the hour component of order_datetime in the orders table.

   Extract the hour from the order_datetime column and count the occurrences for each hour.

   tables: orders

4. What is the distribution of order statuses in the orders table?

   Group by order_status and count the number of orders for each status.

   tables: orders

Table names match the SQLite file and the SQL script.

SELECT c.customer_name, SUM(o.order_total_amount) AS total_spent
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
GROUP BY c.customer_name
ORDER BY total_spent DESC
LIMIT 20;

SELECT STRFTIME('%H', order_datetime) AS order_hour, COUNT(order_id) AS order_count
FROM orders
GROUP BY order_hour
ORDER BY order_count DESC
LIMIT 20;

SELECT order_status, COUNT(order_id) AS status_count
FROM orders
GROUP BY order_status
ORDER BY status_count DESC
LIMIT 20;

SQL

The dataset is provided in SQLite format. The tables are already defined with appropriate data types. Primary and foreign keys are established to facilitate joins between tables. For example, 'orders.customer_id' links to 'customers.customer_id', and 'deliveries.order_id' links to 'orders.order_id'.

• CSV (zip)One CSV file per table, zipped
• Excel workbookOne worksheet per table
• SQLite databaseA ready-to-query database file with every table
• Parquet (zip)One Parquet file per table, zipped
• SQL scriptCREATE TABLE with primary and foreign keys, then INSERTs
• CSVA single CSV file
• JSONA single JSON file