| CPC G06F 18/10 (2023.01) [G06F 18/214 (2023.01); G06Q 10/04 (2013.01)] | 20 Claims |
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1. A computer-implemented method comprising:
obtaining an incoming data point of a time series data set;
performing, via an online data processing engine, decomposition of the incoming data point to determine a first trend component associated with the incoming data point;
determining, via the online data processing engine, a second trend component expected for a data point subsequent to the incoming data point based on a set of trend components including the first trend component and trend components associated with previous data points of the time series data set;
identifying, via the online data processing engine, a seasonality component expected for the data point subsequent to the incoming data point based on a seasonality component associated with a previous corresponding data point;
predicting, via the online data processing engine, the data point subsequent to the incoming data point using the second trend component and the seasonality component, wherein predicting the data point is performed in real time upon obtaining the incoming data point such that a subsequent data point of the time series data set is not used to decompose the incoming data point or forecast the data point; and
providing the predicted data point subsequent to the incoming data point for analysis or display.
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