Overview
This article provides additional information on gauge measures and dimensions.
Measures
Measures are the mathematical portion of a gauge (e.g., count, count distinct, min, max, sum, average) that is aggregated from an existing raw field within your dataset. In the context of data visualization, measures typically map to the Y-axis of a chart. Examples of measures include ticket count, average time to resolution, and total revenue. For instance, you may 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 selected values 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 of 18.
Example
You would like to see which end users create the most ConnectWise Manage service tickets. Currently, you have 100 service tickets from 25 end users in Manage. To display the data, you create a bar chart gauge with the following measures and dimensions:
- Measure: Service Ticket IDs
- Aggregation function: COUNT
- Dimension: end_user
The resulting gauge displays the number of service tickets submitted by each end user and allows you to see which user submitted the most tickets.
BrightGauge provides the following set of predefined aggregations.
Aggregation |
Description |
Result for cells that contain 1, 2, 2, 5, 3 |
Sum |
Computes the sum of the numbers in the measure's cells. Null values are ignored. |
13 |
Average |
Computes the arithmetic mean of the numbers in the measure's cells. Null values are ignored. |
2.6 |
Min |
Selects the smallest number in the measure's cells. Null values are ignored. |
1 |
Max |
Selects the largest number in the measure's cells. Null values are ignored. |
5 |
Count |
Counts the number of values in the measure's cells. |
5 |
Count Distinct |
Counts the number of unique values in the measure's cells. |
4 |
Dimensions
Dimensions group quantitative data (measures) into useful categories (e.g., number of tickets closed by technician). They usually refer to categorical data, such as technician name, ticket status, or even units of time (e.g., day, week, month). These fields typically map to the X-axis in a line chart or vertical bar chart.
For example, 90 days is your dimension. For a non-date range graph like Tickets Closed by Technician, the technician is your dimension since you are trying to measure the number of tickets closed against that dimension.
Comments
4 comments