In many situations the latest value for a metric on a given day is typically the most useful value but there are other possibilities.
Imagine that we are running an online gaming service and we have a data source that can tell us the number of players actively using our service at this moment. We can create an active users metric to track this value every ten minutes. Two KPIs that might be if interest are the average number of users and the maximum number of users.
- On line 1 the ServiceClarity variable metrics is used to get the metric: active users.
- On line 3 the aggregate function average is applied and the value of the KPI is returned as the average number of active users.
- On line 1 the ServiceClarity variable metrics is used to get the metric: active users.
- On line 3 the aggregate function maximum is applied and the value of the KPI is returned as the average number of active users.
ServiceClarity provides a range of aggregation functions that can be applied to metrics and other KPIs:
Latest
var latest = metrics.get('active users').latest()
Average
var average = metrics.get('active users').average()
Maximum
var max = metrics.get('active users').maximum()
Minium
var min = metrics.get('active users').minimum()
Earliest
var first = metrics.get('active users').earliest()
Median
var median = metrics.get('active users').median()
Sum
var total = metrics.get('active users').sum()