Gauge Measures and Dimensions Explained


A measure is a value that is somehow aggregated from an existing raw field within your dataset (count of tickets, average time to resolution, and total revenue are all measures). In the context of data visualization, measures typically map to the Y axis of a chart!!

Measures typically refer to quantitative data, such as number of tickets opened, average time to respond,  utilization rates, etc. For instance, you might calculate the Average Response Time per day over 90 Days.   In this case, the Response Time field is your measure because you want to get the average response time.

Aggregation functions within BrightGauge perform a calculation on a set of values you have selected and result in a single value. For example, a measure that contains the values 2, 5, 4, 1, 6 aggregated as a SUM results in a single value: 18.

How this applies to a bar chart using (ConnectWise as a Datasource for example) is as follows.  If you have 100 Service Tickets from 25 End Users in your data source, you probably want to view the total number of Service Tickets created by each End User so that you can decide which End Users are opening up the most Service Tickets.  For this example, you would select Service Ticket IDs as your Measure and apply the COUNT Aggregation Function.  And you would select the End User field as a Dimension so you can view the Count of Service tickets per End User.

BrightGauge provides a set of predefined aggregations that are shown in the table below.



Result for cells that contain

1, 2, 2, 5, 3


Computes the sum of the numbers in the measure's cells. Null values are ignored.



Computes the arithmetic mean of the numbers in the measure's cells. Null values are ignored.



Selects the smallest number in the measure's cells. Null values are ignored.



Selects the largest number in the measure's cells. Null values are ignored.



Counts the number of values in the measure's cells.


Count Distinct

Counts the number of unique values in the measure's cells.



Dimensions are the slicing and dicing of a Measure.  They usually refer to categorical data, such as technician name, ticket status, or even units of time (e.g., day, week, month). Generally, dimensions are used to group quantitative data (measures) into useful categories (e.g., number of tickets closed by technician).  These fields typically map to the X axis in a line chart or vertical bar chart.

For an example, the 90 days is your Dimension.  And for a non date range graph like “Tickets Closed by Technician”, the Technician is your dimension since you are trying to measure the # of Tickets Closed against that dimension.

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  • Brain,

    Is it possible to have a Date filter for Year to Date?


    Thank You


  • Hi Nataly,

    Our current default datasets only pull back 120 days worth of data so the year to date filter most of time wouldn't pick up all the YTDd data.  So we purposefully did not include that filter to not confuse anyone.

  • When choosing a date field, it seems that the only aggregation option is count. Is this correct?

  • IS it possible to calculate a field? customer + ticket type + subtype for example