Volumetric event forecasting tool

A non-transitory computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

• receiving activity data associated with events that occur in a computer network;
• transforming the received activity data into processed activity data, the processed activity data including data that represents a series of distinct time periods, each distinct time period having a respective event count;
• determining, for each of the distinct time periods, whether the distinct time period is associated with an anomalous level of event activity;
• flagging the processed activity data with a designation of whether each of the series of distinct time periods is associated with the anomalous level of event activity;
• based on the flagged activity data, for a given future time period, generating prediction data that predicts a volume of events for the given future time period and a likelihood that the volume of events for the given future time period will be anomalous;
• and providing the prediction data.

A computing system, comprising:

• one or more processors;
• and
• one or more computer-readable devices including instructions that, when executed by the one or more processors, cause performance of operations including:
• receiving activity data associated with events that occur in a computer network;
• transforming the received activity data into processed activity data, the processed activity data including data that represents a series of distinct time periods, each distinct time period having a respective event count;
• determining, for each of the distinct time periods, whether the distinct time period is associated with an anomalous level of event activity;
• flagging the processed activity data with a designation of whether each of the series of distinct time periods is associated with the anomalous level of event activity;
• based on the flagged activity data, for a given future time period, generating prediction data that predicts a volume of events for the given future time period and a likelihood that the volume of events for the given future time period will be anomalous;
• and
• providing the prediction data.