Think of dimensions as virtual columns or fields in your data model. If you were to do a GROUP BY in SQL, the columns in the GROUP BY part are the dimensions.

Whereas, measures are the aggregation part of a GROUP BY.

Another way to think of dimensions and measures is:

• dimensions you can typically imagine on the x-axis of a bar or line chart
• measures you can typically imagine on the y-axis.

Some examples:

SELECT 
	"country" AS "my country", 
	SUM("price") AS "total price" 
FROM orders 
GROUP BY 1

• “my country” is a dimension
• “total price” is a measure

SELECT 
	COUNT(*) AS "my count" 
	AVG("price" as "average price"
FROM orders

• “my count” and “average price” are both measures

SELECT 
	DATE_TRUNC('week', "created_at") AS "Week",
	MAX("created_at") as "Last order time"
FROM "orders"
GROUP BY 1
ORDER BY 1 DESC

• “Week” is a dimension
• “Last order time” is a measure

Detailed documentation on how to define dimensions and measures in Cube can be found in their official documentation here:

• Dimensions (https://cube.dev/docs/reference/data-model/dimensions)
• Measures (https://cube.dev/docs/reference/data-model/measures)