Several new visualization types have been added into our visualization portfolio. These new additions make 19 different formats that allow our customers to bring in a brand new perspective on the data.
The new visualizations include:
Geo- marker pins
Geo Marker Heatmap renders circles at specified locations on the geo chart, with the color and size that you specify. When hovering above a specific marker it will magnify and show data that you want displayed. Drilldowns can setup to drill into the raw data of each of these widgets as well.
Examples: Usage distribution across cities and areas, with a drilldown into each city
Geo pins: Simple Google map pins based on address.
Along with the Geo – Markers/heat maps you are able to change the map type displayed into 4 new styles: satellite, terrain, roadmap, or hybrid. You are also able to change the primary region you would like to focus on, enter in specific coordinates for an exact address, and magnification level.
The data grid heat map allows users to view the data in multi-dimensions. You are able to track your numbers while comparing them across multiple sources and a specific baseline value set.
Common Use Cases: Cohort Analysis, Quickly identifying areas of strengths and weaknesses across dimensions.Bubble
The Bubble chart is a variation of a scatter plot, but the bubble chart has an added dimension; the size of the bubbles. The X and Y axes are both value axes, and the Z axes is a size value. Bubble charts are useful to use when three data series that each contain a set of values.
Example: Deficit by GDP, by country, with the size of the bubble indicated by GDP.
Enables tracking/progress of goals. Color options can be customized for start/mid/finish.
Example: Sales goals for the quarter.
A Scatter plot display values for two variables for a set of data, since we allow the points to be color-coded you can increase the number of displayed variables to three.
For example a company could plot the amount of transactional emails sent vs the amount of marketing emails sent over a given time period (as shown above).
A spline graph is similar to a line graph; however it possesses a much higher degree of smoothness where the data points connect. The chart calculates a suitable smooth curve between any pair of points which leads to advantages in simplicity and clarity.
Example: Product purchases by type by time.
Along with the new additions, Cloud9 Charts is already offering 12 existing visualizations.
Data Grid Summary: Geo - Regions: