How does R handle large-scale time series forecasting architectures?

R supports time series forecasting through specialized packages and distributed preprocessing pipelines.

Forecasting at scale requires preprocessing pipelines for cleaning, feature engineering, and decomposition. Models like ARIMA, ETS, and Prophet are used, but in enterprise systems, forecasting is distributed across segments or time windows to improve scalability.