About dimensions and measures

In a dataset, data is assigned to one of the following categories:

  • Dimensions
  • Measures

When creating visualizations, you need to select appropriate dimensions and/or measures from a dataset.


Dimensions provide the context or the perspectives used for analyzing the data. They represent grouping, filtering, and labeling criteria. Usually, they are non-numerical items, which help you understand the meaning of numerical information. Common dimensions and corresponding column names include the following:

  • Place – Country, Region, Location, City, State
  • People – Customer, Customer Type, Customer ID, Employee
  • Product – Product, Product Type, Product Line
  • Time – Year, Month, Day, Quarter, Date

In a visualization, dimensions can be combined to provide a different perspective on a measure. For example, you can compare sales for two products, in different countries, over several years.


Measures are sets of numerical values that describe business events. They are usually calculations that apply aggregation functions, such as Sum, Average, or Count, to data records. Common measures include the following:

  • Sales (Sum)
  • Profit (Sum)
  • Sale Price (Avg)
  • Discount (Avg)
  • Gross Sales Variance (Sum)