You may find it useful to define a hierarchy of dimensions, to enable visuals with variable levels of granularity over the same range of data.
This feature is available only to users with administrative privileges.
The following steps demonstrate how to define such a hierarchy on the dataset World
Life Expectancy [data source
samples.world_life_expectancy
]. We will use the dimensions
un_region, un_subregion, and country to define a dimensional hierarchy
called Region.
On the main navigation bar, click Data.
The Data view appears, open on the Datasets tab.
In the Datasets area, select World Life Expectancy (samples.world_life_expectancy)
.
In the Dataset Detail menu, select Fields.
In the Fields interface, select Edit fields.
un_region
.Click (down) icon on the un_region
line, and select Create Hierarchy.
In the Create Hierarchy modal window, enter the values for Hierarchy Name and Hierarchy Comment, and click Create.
We named our hierarchy Region, and described it as Geographical Granularity.
Note that Measures now contain a hierarchy
Region, denoted by the
(hierarchy) icon. The hierarchy contains a single element, un_region
.
To add more levels to the hierarchy, simply click and drag the relevant dimensions or measures to the newly created hierarchy. Be sure to arrange them in order of scale, from largest to smallest.
Below un_region
, we added un_subregion
.
Below un_subregion
, we added country
.
Click Save.
Note that the hierarchy Region appears alongside the dimensions obtained directly from the data table.
Defined dimension hierarchies, such as Region that we created here, can be used just as any other dimension field of the dataset.