datawindowing
Data windowing is a technique in data processing that applies a defined window to a sequence of observations to enable analysis over subsets. In time series and streaming contexts, a window specifies a contiguous block of data points, defined either by time duration or by a fixed number of samples, and can be overlapping or discrete. The approach is widely used to compute statistics and features on recent data without reprocessing the entire series.
Common window types include time-based tumbling windows, which partition data into non-overlapping intervals; sliding windows, which
Implementation typically relies on windowing constructs in databases and streaming engines. SQL window functions compute aggregates
Applications of data windowing include computing moving averages, volatility, and rate metrics; feature extraction for machine
Overall, data windowing is a foundational technique in time-series analytics, real-time monitoring, and streaming data processing,