International Business Machines Corporation
IDENTIFYING ANOMALIES IN DATA DURING DATA OUTAGE

Abstract:

A computer-implemented method, system and computer program product for identifying anomalies in data during a data outage. An anomaly detection model is built using data received from a sensor at a characterized granularity. Once a period of service occurs following a data outage, a quantum of missing data during the data outage is identified using predictive modeling if the data during the data outage is not available at the granularity in which the anomaly detection model is built. The identified quantum of missing data is retrofitted into a predicted pattern during the data outage and the analytics are then re-run on the retrofitted quantum of missing data in the predicted pattern to identify anomalies during the data outage. In this manner, anomalies in data, such as data from sensor readings, can be identified during the data outage thereby enabling the model to provide more accurate predictions of anomalies occurring during the data outage.