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# Release Goals:

• Enhancing users ability to display data in new ways - Enhance chart types and configurations for easy use and creation.

# New Features:

• Combination Charts: A combination chart empowers the user to graph two data elements on the same graph.  It is effectively used for comparison purposes.  For example, a combination graph is recommended to graphically display:
1. Business: Goal revenue vs. Actual revenue by month
2. K-12: Total Absences vs. Unexcused Absences; or Average Math Test Scores vs. Average English Test Scores; or Writing Scores vs. Total Absences; etc.
3. Higher Ed: Total Revenue vs. Total Expenses
4. Finance: Max open vs Total Volume

The first data element plotted in a combination chart appears as a bar chart; the second (and subsequent) appear as line graphs.  All standard features apply to a combination chart including the ability to apply a series, a filter, customize the Y-axis and include a benchmark.

• Dual Y-axis Combination Charts: This chart is similar to a combination chart (above); however, it differs to the extent that you can apply two different Y-axis scales.  It is recommended when you are graphing multiple data elements that have a significant different scales.  For example:
1. Business: Total sales vs. Total Revenue by month
2. K-12: Total number of tests taken (which may range from 1,000 – 10,000) vs. Average Math Test Scores (which may range from 0-100)
3. Higher Education: Total Expenses vs Total Enrolled at the University or Total Number of Students who Applied vs. Total Number of Students Accepted
4. Finance: Max open vs yield %

All standard features are available with the Dual Y-Axis Combination Chart.  As a user, you can apply a customized Y-axis (to the right and left), enter a benchmark, add a series (to one of both of the data elements in the graph), and filter by any field.

• Scatter plot:  A Scatter plot is used to plot data points on a horizontal and a vertical axis in the attempt to show how much one variable is affected by another. Each row in the data table is represented by a marker whose position depends on its values in the columns set on the X- and Y-axes. Multiple scales can be used on the Y-axis to when you want to compare several markers with significantly different value ranges.

• Gauges: Gauges make for great gadgets on the dashboard.  Users can publish key data metrics as a thermometer, linear/angular gauges as well as many other interesting, eye-catching gauges.  Creating a gauge is easy and users have all standard options available such as filtering and applying a benchmark.  Below are few examples of gauges:
1. Total number of tests delivered
2. Average writing scores compared to the proficiency benchmark
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