US 2019/0102718 A1 · TECHNIQUES FOR AUTOMATED SIGNAL AND ANOMALY DETECTION

Abstract

Predictive analysis techniques are described herein as applied to business variables. In some embodiments, a dynamic dependency model may be generated using a time-series data from a first time period. The model may define relationships between business variables during the first time period. A prediction of values of a variable (e.g., a business variable such as sales, revenue, attrition, or the like) can be generated based on the dynamic dependency model. The prediction of values may be for a second time period after the first time period. The actual values of the variable over the second time period can be obtained and compared to the predicted values to generate a statistical deviation. The statistical deviation may exceed a threshold and, a notification of the statistical deviation may be transmitted to a user device. The notification may alert the user that the variable is likely to miss the targeted/predicted value.

Claims18

Dependent claims

A method comprising:

generating, by a computer system, a dynamic dependency model using a first set of time-series data, wherein the dynamic dependency model defines a plurality of relationships between a plurality of variables related to an enterprise, and wherein the first set of time-series data is collected for a first time period;
generating, by the computer system, a prediction of a first plurality of values of a first variable of the plurality of variables based on the dynamic dependency model, wherein the first plurality of values are predicted for a second time period;
obtaining, by the computer system, a plurality of actual values of the first variable during the second time period;
comparing, by the computer system, the first plurality of values with the plurality of actual values to generate a statistical deviation;
identifying, by the computer system, the statistical deviation as an anomaly;
and
transmitting, by the computer system, a notification of the anomaly to a user device.

4 more elements

A non-transitory computer-readable memory storing a plurality of instructions executable by one or more processors, the plurality of instructions comprising instructions that when executed by the one or more processors cause the one or more processors to perform processing comprising:

generating a dynamic dependency model using a first set of time-series data, wherein the dynamic dependency model defines a plurality of relationships between a plurality of variables related to an enterprise, and wherein the first set of time-series data is collected for a first time period;
generating a prediction of a first plurality of values of a first variable of the plurality of variables based on the dynamic dependency model, wherein the first plurality of values are predicted for a second time period;
obtaining a plurality of actual values of the first variable during the second time period;
comparing the first plurality of values with the plurality of actual values to generate a statistical deviation;
determining that the statistical deviation exceeds a threshold;
and
transmitting a notification of the statistical deviation to a user device.

4 more elements

A system comprising:

one or more processors;
a memory coupled to the one or more processors, the memory storing a plurality of instructions executable by the one or more processors, the plurality of instructions comprising instructions that when executed by the one or more processors cause the one or more processors to perform processing comprising:
generating a dynamic dependency model using a first set of time-series data, wherein the dynamic dependency model defines a plurality of relationships between a plurality of variables related to an enterprise, and wherein the first set of time-series data is collected for a first time period;
generating a prediction of a first plurality of values of a first variable of the plurality of variables based on the dynamic dependency model, wherein the first plurality of values are predicted for a second time period, wherein the second time period is after the first time period;
obtaining a plurality of actual values of the first variable during the second time period;
comparing the first plurality of values with the plurality of actual values to generate a statistical deviation;
determining that the statistical deviation exceeds a threshold;
and
transmitting a notification of the statistical deviation to a user device.

6 more elements

Dependencies are inferred from the claim text.

Techniques for automated signal and anomaly detection

Life of this patent

Techniques for automated signal and anomaly detection

Life of this patent

Abstract

Claims18