Which region carried the quarter — and which one is coming up fast?
West generated the highest revenue while East showed the strongest late-period growth — up 38% from June to July, against 10% for West.
West leads the two-month total; the gap to North is $7.8k.
bar · 1 dimension, 1 measure · 4 rows · highlight: West · filters: Order date
SELECT region,
ROUND(SUM(revenue) / 1000.0, 1) AS revenue_k
FROM sales
WHERE order_date BETWEEN '2026-06-01' AND '2026-07-31'
GROUP BY region
ORDER BY revenue_k DESC
| region | revenue_k |
|---|---|
| West | 58.9 |
| North | 51.1 |
| East | 47.2 |
| South | 39.2 |
Totals flatter the West — it has the region's two biggest accounts and it started the period ahead. The more interesting movement is underneath the totals: month-on-month, the order is not the same as the standings.
East gains $7.6k month-on-month — the largest absolute and relative jump of any region.
line · 1 date, 1 measure, by region · 8 rows · highlight: East · filters: Order date
SELECT substr(order_date, 1, 7) AS month,
region,
ROUND(SUM(revenue) / 1000.0, 1) AS revenue_k
FROM sales
WHERE order_date BETWEEN '2026-06-01' AND '2026-07-31'
GROUP BY month, region
ORDER BY month, region
| month | region | revenue_k |
|---|---|---|
| 2026-06 | East | 19.8 |
| 2026-06 | North | 24.1 |
| 2026-06 | South | 16.7 |
| 2026-06 | West | 28.0 |
| 2026-07 | East | 27.4 |
| 2026-07 | North | 27.0 |
| 2026-07 | South | 22.5 |
| 2026-07 | West | 30.9 |
If July's pace holds, East passes North within a month and challenges West by autumn. The recommendation that follows: protect the West accounts, but put the incremental sales effort where the slope is — East. The queries above are the argument; run them against next month's orders and the write-up updates itself.
Source: demonstration dataset — 43 orders across 6 products, prepared as orders + products → sales (42 rows; one orphan order excluded by the join).