Modeling: Measures and Dimensions

Models in SAP Analytics Cloud contain rows and columns of data, and every column in a model is defined as a dimension or a measure.

What’s the difference between a measure and dimension?

Measures are numerical values that mathematical functions work on. For example, a sales revenue column is a measure because you can find out a total or average the data.

Dimensions are qualitative and do not total a sum. For example, sales region, employee, location, or date are dimensions.

When dimensions and measures work together, they help answer complex business questions. For example, take a look at the visualizations below.

Chart 1 Chart 2
Chart showing the measure total of sales revenue Chart showing the measure of "sales revenue" in relation to the dimension of "region"

Chart 1 visualizes a single measure, in this case, “revenue”. The visualization only answers one question: how much profit did we make? Chart 2 visualizes the measure “revenue” in relation to the dimension “region” to show profits by region. Exploring profits by region will help answer questions about regional performance.

So, are all numbers measures?

No. Not all columns containing numerical data are considered measures. A satisfaction rating, for example, makes more sense as a dimension. Say your model has a column that contains product ratings out of 5-stars. Knowing that a certain product line received 10,000 stars in total is not particularly interesting. However, knowing which products in that line received the most 5-star ratings is useful.

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