Heat Matrix data visualizations display trends and correlations
Heatmap data visualization. It is an excellent choice if your data items can be categorized into multiple groupings (for example, By Region and By Product), and you want to understand the correlation between these groupings. A Heat Matrix is similar to a Heatmap or a Treemap visualization in that it displays many different data items and it can represent the value for each item using colors. However, unlike a Heatmap or a Treemap, the Heat Matrix has a defined structure where two data attributes define each data item, thus producing a matrix. Within the Heat Matrix, each column and row represents a unique attribute, and the point where two items intersect represents a unique combination of the two attributes.The Heat Matrix is closely related to the
Analyze large data matrices
In a Heat Matrix, each point is represented as an equally sized box, with the value of the item represented by color. The user can alter the color scale as needed to make it easier to see outliers and trends. By contrast to Heatmaps and Treemaps which re-tessellate when resized, the location of each item in the Heat Matrix is fixed and that location in itself conveys useful information, since the location has defined horizontal and vertical coordinates and will not change, regardless of how the Heat Matrix is resized.
Look at cross rates, market risk and other types of data
The Heat Matrix information visualization is useful in a large number of industries. It is commonly used in financial services applications to look at Foreign Exchange Cross Rates and Market Risk. A typical corporate application is to look at sales revenue and/or profitability across regions and product lines.