Q11📊Agregasi & Grouping★☆☆☆☆Copy-pasteSafe to Run
Revenue by Single Dimension
Dialect:bigquerypostgresqlsnowflakemysql
#revenue#aggregation#group-by#dimension
Kapan Pakai Query Ini
Query paling dasar di toolkit seorang analyst. Kamu pakai ini setiap kali mau lihat revenue dipecah per satu dimensi. Bisa per produk, per region, per channel, per sales rep, atau dimensi apapun yang relevan. Cocok banget buat laporan rutin, quick sanity check distribusi, atau mulai investigasi kenapa angka total nggak sesuai ekspektasi.
Yang Perlu Diganti
your_schema.orders→ nama tabel transaksi kamuproduct_name→ kolom dimensi yang mau kamu group (misal:region,channel,category,salesperson_id)revenue→ kolom nilai yang mau dijumlah (misal:order_value,gmv,net_sales)status = 'completed'→ filter status transaksi yang valid di sistem kamu (hapus kalau nggak perlu filter)
Query
SELECT product_name, COUNT(*) AS total_orders, SUM(revenue) AS total_revenue, ROUND(AVG(revenue), 2) AS avg_order_value, MIN(revenue) AS min_order_value, MAX(revenue) AS max_order_value FROM your_schema.orders WHERE status = 'completed' GROUP BY product_name ORDER BY total_revenue DESC;
Contoh Output
| product_name | total_orders | total_revenue | avg_order_value | min_order_value | max_order_value |
|---|---|---|---|---|---|
| Premium Membership | 8,420 | 421,000,000 | 50,000.00 | 50,000 | 50,000 |
| Basic Plan | 24,310 | 364,650,000 | 15,000.00 | 15,000 | 15,000 |
| Add-on Storage | 5,890 | 88,350,000 | 15,000.00 | 5,000 | 50,000 |
| One-time Setup | 1,230 | 24,600,000 | 20,000.00 | 10,000 | 100,000 |
Variasi
- Tambah
WHERE created_at BETWEEN '2024-01-01' AND '2024-12-31'untuk scope ke periode tertentu - Ganti
ORDER BY total_revenue DESCdenganORDER BY product_name ASCkalau kamu butuh urutan alfabetis untuk laporan - Tambah
HAVING total_orders >= 100untuk menyaring dimensi dengan volume rendah yang bisa noise - Ganti
SUM(revenue)denganSUM(revenue) / 1000000dan aliastotal_revenue_jutabiar angka lebih mudah dibaca di laporan
Variasi Dialect
Sama di semua dialect. ANSI SQL standard.