Generate AI SQL Query in Seconds

SELECT 
    c.customer_id,
    c.name,
    COUNT(o.order_id) as total_orders,
    SUM(o.total_amount) as lifetime_value,
    AVG(o.total_amount) as avg_order_value
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
GROUP BY c.customer_id, c.name
HAVING COUNT(o.order_id) > 5
ORDER BY lifetime_value DESC;

WITH product_sales AS (
    SELECT 
        p.product_id,
        p.name,
        COUNT(o.order_id) as order_count,
        SUM(oi.quantity) as total_quantity_sold
    FROM products p
    JOIN order_items oi ON p.product_id = oi.product_id
    JOIN orders o ON oi.order_id = o.order_id
    WHERE o.order_date >= DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY)
    GROUP BY p.product_id, p.name
)
SELECT 
    ps.*,
    p.current_stock,
    p.reorder_level,
    CASE 
        WHEN p.current_stock <= p.reorder_level THEN 'Need to reorder'
        WHEN p.current_stock <= p.reorder_level * 1.5 THEN 'Low stock'
        ELSE 'Stock OK'
    END as stock_status
FROM product_sales ps
JOIN products p ON ps.product_id = p.product_id
ORDER BY total_quantity_sold DESC;

SELECT 
    r.region_name,
    c.category_name,
    COUNT(DISTINCT o.order_id) as total_orders,
    SUM(oi.quantity * oi.unit_price) as total_revenue,
    AVG(oi.quantity * oi.unit_price) as avg_order_value
FROM regions r
JOIN customers cu ON r.region_id = cu.region_id
JOIN orders o ON cu.customer_id = o.customer_id
JOIN order_items oi ON o.order_id = oi.order_id
JOIN products p ON oi.product_id = p.product_id
JOIN categories c ON p.category_id = c.category_id
WHERE o.order_date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
GROUP BY r.region_name, c.category_name
ORDER BY total_revenue DESC;