You can visualize all of your data on one Dashboard regardless of whether the data is stored in multiple data tables or only one. Below we will walk you through the steps for creating a Dashboard using any data table across all of your data sets in UpMetrics.
1) Add some data
If you haven't done so already, upload or import your data sources into UpMetrics via our CSV upload or through the integrations. In our example here, we are using sample data showcasing a volunteer program here at UpMetrics. We have three tables across two data sets for program tracking, survey responses, and volunteer registration - all of which are related conceptually but have no way of linking to each other.
2) Create a dashboard
Creating a Dashboard is the same as before. You will select a data source to start with, but you can add Widgets from any other table once the Dashboard is created. Here we are starting with our "Program Participation"
3) Add Widgets
Once your Dashboard is created, you will see that there is now an option called "Data Source Settings" when you go to add a Widget. The default will be the data source you selected when created the Dashboard, but you can select any table from any data set in your account.
4) Setting filters
When you set filters on your Dashboard now, you will see that there are options for every data source linked to the Dashboard.
When a data source is selected, the corresponding Widgets that will be affected will be highlighted in orange.
When filters on a data source are applied, the label itself will also be highlighted in orange to indicate which source have filters actively applied. The filter label that is currently selected will be highlighted in blue.
Filters have to be set independently for each data source. For example, suppose we want the ENTIRE Dashboard to show data for a specific gender. We'll select female from our "Participant Data" source.
If you'll notice, the Widget for "Participant Gender Breakdown" now shows only data females, but "Staff Gender Breakdown" still shows data for all genders. This is because the data for "Staff Gender Breakdown" comes from a different data source. In order to show only a subset of data across all data sources, the filters have to be set for each.
