Analyzing data using record map point clusters​

Clustered point maps automatically groups sets of points (based on their latitude-longitude coordinates) that are close to each other on the map. Clusters are aggregations (like categories or numerical bins), and they can be measured and then visualized to show the results. Point clusters visualize data using color and size, and you can change both the point size and point color settings.

Selecting cluster measurement

Clusters can be measured using count or sum functions. You can also use the (None) option for either color or size in any analysis setting.

Special Features

• The pop-up for each cluster shows the data within the cluster, including the measurement you've enabled like sum or count. This feature is similar to other aggregates such as categories or numeric ranges.

Constraints

• You cannot enable an average measurement function when point clusters are shown.
• Since the measurement function is applied to the whole dashboard, you cannot select different numeric  attributes for the size and color attributes when using the sum function. You also cannot choose sum for one attribute size or color, and count for another.

Navigating map using clusters

Clicking on a cluster zooms into the cluster area. This provides a quick cluster-based navigation alternative to using + buttons or double-clicking on the map area.

Special Features

• The size and color of the clusters and points are based on the visible set of clusters and zoom level. This effectively filters the map and re-scales the colors accordingly.
• While this may cause changes in visualization in different zoom levels or after panning, this approach displays a more optimum visualization in a current map view by normalizing the size and color to the data visible in the map.