RANK() OVER (
    [PARTITION BY partition_column]
    ORDER BY order_column [ASC|DESC]
)

DENSE_RANK() OVER (
    [PARTITION BY partition_column]
    ORDER BY order_column [ASC|DESC]
)

NTILE(n) OVER (
    [PARTITION BY partition_column]
    ORDER BY order_column [ASC|DESC]
)

SELECT 
    region,
    employee_name,
    sales_amount,
    RANK() OVER (PARTITION BY region ORDER BY sales_amount DESC) as sales_rank,
    DENSE_RANK() OVER (PARTITION BY region ORDER BY sales_amount DESC) as dense_sales_rank
FROM sales_data
ORDER BY region,

SELECT 
    category,
    product_name,
    revenue,
    RANK() OVER (PARTITION BY category ORDER BY revenue DESC) as revenue_rank
FROM product_sales
QUALIFY RANK() OVER (PARTITION BY category ORDER BY revenue DESC) <= 3
ORDER BY category,

SELECT category, product_name, revenue, revenue_rank
FROM (
    SELECT 
        category,
        product_name,
        revenue,
        RANK() OVER (PARTITION BY category ORDER BY revenue DESC) as revenue_rank
    FROM product_sales
)
WHERE revenue_rank <= 3
ORDER BY category,

SELECT 
    customer_id,
    customer_name,
    lifetime_value,
    NTILE(4) OVER (ORDER BY lifetime_value DESC) as quartile,
    CASE NTILE(4) OVER (ORDER BY lifetime_value DESC)
        WHEN 1 THEN 'Top 25% (VIP)'
        WHEN 2 THEN 'Upper 25%'
        WHEN 3 THEN 'Lower 25%'
        WHEN 4 THEN 'Bottom 25%'
    END as customer_segment
FROM customers
ORDER BY lifetime_value DESC

SELECT 
    employee_id,
    employee_name,
    sales_amount,
    customer_satisfaction,
    -- Rank by sales
    RANK() OVER (ORDER BY sales_amount DESC) as sales_rank,
    -- Rank by satisfaction
    RANK() OVER (ORDER BY customer_satisfaction DESC) as satisfaction_rank,
    -- Combined score rank
    RANK() OVER (ORDER BY (sales_amount * 0.6 + customer_satisfaction * 0.4) DESC) as combined_rank,
    -- Decile grouping
    NTILE(10) OVER (ORDER BY sales_amount DESC) as sales_decile
FROM employee_performance
ORDER BY

WITH customer_segments AS (
    SELECT 
        customer_id,
        order_count,
        total_revenue,
        NTILE(100) OVER (ORDER BY total_revenue DESC) as percentile
    FROM customer_metrics
)
SELECT 
    CASE 
        WHEN percentile <= 10 THEN 'Top 10%'
        WHEN percentile <= 25 THEN 'Top 25%'
        WHEN percentile <= 50 THEN 'Top 50%'
        ELSE 'Bottom 50%'
    END as segment,
    COUNT(*) as customer_count,
    AVG(total_revenue) as avg_revenue,
    MIN(total_revenue) as min_revenue,
    MAX(total_revenue) as max_revenue
FROM customer_segments
GROUP BY 
    CASE 
        WHEN percentile <= 10 THEN 'Top 10%'
        WHEN percentile <= 25 THEN 'Top 25%'
        WHEN percentile <= 50 THEN 'Top 50%'
        ELSE 'Bottom 50%'
    END
ORDER BY MIN(total_revenue) DESC

SELECT 
    product_id,
    product_name,
    year,
    annual_sales,
    RANK() OVER (PARTITION BY year ORDER BY annual_sales DESC) as yearly_rank,
    LAG(RANK() OVER (PARTITION BY year ORDER BY annual_sales DESC)) 
        OVER (PARTITION BY product_id ORDER BY year) as previous_year_rank,
    RANK() OVER (PARTITION BY year ORDER BY annual_sales DESC) -
    LAG(RANK() OVER (PARTITION BY year ORDER BY annual_sales DESC)) 
        OVER (PARTITION BY product_id ORDER BY year) as rank_change
FROM product_annual_sales
ORDER BY year DESC,