Within Insight a user with permissions of Admin or Creator has the ability to create a visual from data sources such as Core Data, Beacon, Course Evaluation, etc... in a few different ways and can combine typically disparate sources of data together in a single visualization.

Insight supports displaying data in the following formats:

  • Text
  • Table
  • Column
  • Bar
  • Line
  • Donut
  • Scatter
  • Area

How a user chooses to visualize data will depend on the chosen measure(s), as well as if one or more dimensions are used and/or filters applied. The minimum for creating a data visual within Insight is a single measure. Below you can see that I have chosen the current sum of attempted credit hours for the entire institution as my measure Insight display 8,510. Because we have chosen only a single measure, which contains only a single data point, Insight will only display this as text.

Let’s add a dimension and see how we can add more context to this number.




Viewing only a meausre, in this case, Current Sum of Attempted Credit Hours may be useful in answering certain questions, but let’s see what happens when we add a dimension (College(s)/School(s)) and see what that can tell us about this data. From the visual below you will see that we have added the dimension College(s)/School(s). Adding a dimension to a measure provides me with a new set of display options, here I have chosen to display my data as a bar chart.




We can take this visualization a step further by adding a second dimension. Below you can see that I have added a student organization type as my second dimension and changed my visual from a simple bar chart to a stacked bar chart, as well as changed the color to improve my visualization.


Filters can be a powerful addition to take your visualization to a more granular level of specificity. Unlike a Dimension and Slices that add data points to your Measure(s) for displaying your data in a variety of combinations, Filters work to remove certain aspects of your data from the overall visualization.  

To illustrate how Filters work we will continue our example from our visualization above. Things are beginning to look great and we are now displaying the attempted credit hours for the Business School and the College of Arts and Sciences. Perhaps we want to get more specific with our visual and only students who enter the institution with a GPA between 2.0 and 3.0. With Insight's filters, this is an easy task.

The GIF below shows you how to apply filters to our visualization in order to meet that criterion. In this example, we are using the logic of finding students who had an incoming GPA that is greater than or equal to 2.0, which sets our lower bound. THen we want to use the or logic of students who had an incoming GPA that is less than or equal to 3.0, which sets our upper bound. You can use this logic and many more variables to really dig into your institution's data.




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