Dimension & Dimension Values
What is a Dimension?
Dimension is the qualitative information of the data, while metric is the quantity of the data. Metrics become meaningful within the context of a set of dimensions. For example, a revenue of 300 is not meaningful by itself. When you put a revenue metric in the context of dimensions, such as Region and Time, the measure becomes meaningful: the revenue for New York in January is 300.
What makes a Dimension?
Dimensions come from attributes available in your raw data, usually categorical data columns (like Region, Segment or Age Group). The column is the dimension, while each of the raw values in the column can be a dimension value.
For example, when you query Revenue by City New York this year, you are essentially asking: give me the SUM number for all values of column rev_amount that has the value "New York" in the column "City" and has its transaction date within this year. In this case, City is your dimension and New York is the specific Dimension Value.
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