You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I should be able to run anomaly detection on metrics that are not additive.
Below are a few examples of aggregate functions in a dataset's SQL GROUP BY that can then be supported:
COUNT(DISTINCT)
MIN()
MAX()
AVG()
Custom Percentage calculations
Dataset SQL can have zero or 1+ dimensions. Since data cannot be rolled up, anomaly definition cannot define anomaly explosion. Instead, dataset SQL itself defines the extent of explosion.
e.g. Say a dataset has 2 dimensions and 1 metric - State, Brand, ConversionRate. This means anomaly objects must be created for each state+brand combination. We cannot have an anomaly definition for a single dimension or no dimension.
impacts Anomaly Definition screen and logic
impacts anomaly object creation process
RCA must be disabled for such anomaly cards
The text was updated successfully, but these errors were encountered:
I should be able to run anomaly detection on metrics that are not additive.
Below are a few examples of aggregate functions in a dataset's SQL GROUP BY that can then be supported:
COUNT(DISTINCT)
MIN()
MAX()
AVG()
Custom Percentage calculations
Dataset SQL can have zero or 1+ dimensions. Since data cannot be rolled up, anomaly definition cannot define anomaly explosion. Instead, dataset SQL itself defines the extent of explosion.
e.g. Say a dataset has 2 dimensions and 1 metric - State, Brand, ConversionRate. This means anomaly objects must be created for each state+brand combination. We cannot have an anomaly definition for a single dimension or no dimension.
The text was updated successfully, but these errors were encountered: