WITH ranked_videos AS (
    SELECT
        video_title,
        category,
        views,
        ROW_NUMBER() OVER (
            PARTITION BY category
            ORDER BY views DESC
        ) AS rn
    FROM videos
)
SELECT
    video_title,
    category,
    views
FROM ranked_videos
WHERE rn = 1;

💡 Example 4: Calculate Channel Performance 

SELECT
    c.channel_name,
    COUNT(v.video_id) AS total_videos,
    SUM(v.views) AS total_views,
    SUM(v.likes) AS total_likes,
    SUM(v.comments) AS total_comments
FROM channels c
LEFT JOIN videos v
    ON c.channel_id = v.channel_id
GROUP BY c.channel_name
ORDER BY total_views DESC;

💡 Example 5: Analyze Publishing Performance 

SELECT
    EXTRACT(DOW FROM publish_date) AS day_of_week,
    COUNT(*) AS total_videos,
    ROUND(AVG(views), 0) AS avg_views
FROM videos
GROUP BY EXTRACT(DOW FROM publish_date)
ORDER BY avg_views DESC;

💡 Example 6: Rank Videos by Views 

SELECT
    video_title,
    views,
    DENSE_RANK() OVER (
        ORDER BY views DESC
    ) AS view_rank
FROM videos;

🎯 Key Insights You Can Derive

🔹 Which videos generate the most views? 
🔹 Which content categories perform best? 
🔹 Which videos have high engagement but relatively low views? 
🔹 What publishing days generate the most views? 
🔹 Which channels have the strongest audience engagement? 
🔹 Which content contributes most to subscriber growth? 
🔹 Which videos should be promoted further? 

💼 This project is especially useful for Data Analysts, Product Analysts, Growth Analysts, Marketing Analysts, and Business Intelligence professionals working with content, media, and digital platforms.

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