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Dimension represents the angle or aspect of data classification. City is a dimension, month is a dimension, and data range is also a dimension. Multi-dimensional thinking is consistent with human habits. Three-dimensional thinking is most frequently used. Three dimensions can form a cube. Slice refers to the slice of a cube. For example, data from all cities in January constitute a surface. Dice refers to dice of a cube. For example, Beijing's data in January form a small cube. You can also view the dimension as a group. Group them, and summarize the numeric types. The data types commonly used as dimensions include:

 

The ranking function of the dimension is more meaningful. Especially the advanced sort can support the sorting based on aggregation of other fields, and can also be ranked. The detail data does not have this function. Only the aggregated data can be ranked.

 

Dimension can be converted into measure. The data connection module interface can be modified, only limiting to change of the whole data set level. All the places using dashboard are determined as dimension or measurement by means of data set division. There is also another place can be converted between dimension and measurement. On the object's binding interface, which is just the object itself. But after cut the dimensional field into measurement, statistics functions supported only seek for the maximum, minimum, number of statistics, statistical number of different values, and the approximate number of different values. This is because It doesn't make sense to sum up the fields of non-numeric type. But it makes sense to take the maximum, minimum, number of statistics, counting the exact different values and different counting values.