A treemap is used for displaying huge amounts of data that can be structured hierarchically (tree-structured data). It presents the data using differently sized and colored rectangles.

Data in a treemap is organized hierarchically. Each branch in the hierarchy is symbolized by a rectangle, which in turn is divided into smaller rectangles representing sublevels or sub-branches. Within the different hierarchy levels, the rectangles are sized proportionally by the values in a numerical data column, for example, a sales column. The largest rectangle is positioned in the top left corner and the smallest rectangle in the bottom right corner.

For example, below you can see the hierarchy used in the treemap above:

The entire visualization space is used, which makes it possible to present a large amount of data simultaneously. This makes it easy to spot patterns and irregularities in your data by a quick look.

The sizes of the rectangles represent numerical data. Also, the colors of the rectangles can reflect numerical data by changing gradually between a color representing the maximum value of your data and another color representing the minimum value. You can choose the same data column for both sizing and coloring, or different data columns. In the treemap above, the sizes of the rectangles reflect one data column, and the colors another.

The different settings that define the treemap are found in the legend or in the visualization properties; the Hierarchy axis, the Size axis, and the Color axis. See Creating a treemap for more details about the configuration.

All visualizations can be configured to show data limited by one or more markings in other visualizations only (details visualizations). Treemaps can also be limited by one or more filterings. Another alternative is to configure a treemap without any filtering at all. See Adding data limitations for a visualization for more information.

You can show data from multiple data tables in the same visualization if a proper data table matching is available. For more information, see Multiple data tables in one visualization and Column matches.