Creating a report visualization

You can customize your reports and choose the data and filters you need to gain specific insights into your program. Reports include visualizations that can be added to your custom dashboards.

To start exploring your data, open the navigation bar on the left and go to Explore. If you have one or more of Benevity’s products, you’ll see them listed here. Choose a product to access your program data.

Within the product Explore, you’ll see some Quick Start templates that are ready for you to use. Check out their descriptions as there might be one you can start with! 

If you’d prefer to create a new report, the first step is to add some data. 

Adding Data

The left navigation panel displays an expandable list of All Fields that are available to add to the data table. You can browse Dimensions and Measures in this list or search for a field by entering the name in the Find a Field search bar. Select a field name to add it to the data table and then Run in the top right to generate results when you include a new field. 

  • Dimensions are attributes of your data and contain qualitative values. They define what data you want (e.g., date, region).
  • Measures are quantitative data (e.g., number of payments, budget amount). 

If you're unsure of the definition of a field, hover over the column header in the data table or select the information icon (if displayed) next to the field name in the list on the left.

You can create custom fields and table calculations for more specific insights. When fields are added to the data table, you can find them in the In Use field list. 

Formatting the data table

There are several options available at the top of the Data table or in the column header menu to format your data: 

  • Row Limit: enter the number of rows you want to limit the data to. This can cut data loading time. 
  • Totals: select this checkbox to show totals for each row. 
  • Subtotals: select this checkbox to show subtotals for a grouping of data. 
  • Reorder columns by selecting the header and dragging it to a new position. 
  • Sort columns by selecting the column header. Hold Shift while selecting multiple columns to sort by more than one column in order. 
  • Remove a column by selecting the cog icon in the header and choosing Remove.
  • Hide a field from the visualization by selecting the cog icon in the header and choosing Hide this field from visualization.
  • Create a Pivot table by selecting the cog icon on a dimension column header and choosing Pivot. You'll need to run the report again to see the values change. 

Grouping data

You can group data by selecting the cog icon on a dimension column header and choosing Group. Define the criteria for each group by entering a Group Name and specifying the condition for Group values. Select the Group remaining values checkbox to group all remaining data not included in a specified group. 

Finally, enter a Field name that will appear at the top of the grouped column. You can add an optional description. Select Save and then Run to see the grouped values. 

Applying filters

You can apply filters to refine the data for the insights you need. There are two ways to apply a filter to a data field:

  • Select the Cog icon > Filter on the field column header. 
  • Locate a field from the field lists and select the three-line filter icon next to the field name. 

Filters are displayed at the top of the page. You can set filters based on various conditions like equals, not equals, greater than, less than, etc. You can then enter the specific values or select from the given options, depending on the field type. For date fields, you can often choose relative dates (like "last 7 days") or specific date ranges.

If you're a more advanced user, you can select the Custom Filter checkbox at the top right of the filters view. This allows you to create custom table calculations for filters. Help is available next to the input box. 

After setting your filter criteria, select Run in the top right of the Explore view to apply these filters to your data query. The results are updated to reflect your filters.

Choosing a visualization

Visualizations are powerful tools for representing data in a more insightful manner. They can transform complex datasets into clear, interpretable charts, graphs, tables, and more. A variety of types can be selected for your data at the top of the visualization, including bar charts, line graphs, pie charts, scatter plots, tables, and more.

Make sure that the data you're analyzing suits the type of visualization you choose. For instance, time series data is often best represented in line graphs, while categorical data can be effectively displayed in bar charts. Some visualizations allow for interaction, like hovering over elements to see more data, selecting data to drill down, or filtering directly through the visualization. 

Customizing Visualizations

After selecting a type, customize using the Edit option on the right side. Options might include adjusting axes, changing color schemes, modifying labels, and setting sorting options.


The Forecast feature found next to the visualization Edit uses results in the data table to calculate future data points. Any results that are not displayed because of row limits are not included.

To create a forecast, the data must meet these requirements:

  • Include exactly one timeframe dimension, with dimension fill enabled.
  • Include at least one measure or custom measure (a forecast can include up to five measures or custom measures).
  • Sort results by the timeframe dimension in descending order.

Forecast settings: 

  • Select field: Choose up to five measures from your query for forecasting.
  • Length: Set how far into the future you want to forecast. Shorter forecast lengths generally yield more precise forecasts.
  • Prediction Interval: Decide the confidence level of the forecast, such as 95%, which shows the likely range where the forecasted values will fall.
  • Seasonality: Adjust for repeating patterns in your data, choosing from Automatic, Custom, or None. Automatic detects patterns like daily or monthly cycles. Custom allows you to specify the exact cycle length if you know it.

Saving your report

When you are satisfied with your data and visualization type, select the cog in the top right and choose Save. You have several options:

  • As a new dashboard: Create a new dashboard with this report visualization. 
  • To an existing dashboard: Choose an existing dashboard to add the report visualization to. 
  • As a Look: Saves the report as a Look. This option does not add it to a dashboard. 

These options allow you to navigate your folders to locate a dashboard or save as a Look. Directly saving a report visualization to a dashboard, rather than as a Look, means it will only exist in the dashboard and can't be found in your folders. Any modifications will only impact the dashboard version.

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