BigQuery ML TimesFM models now in preview

Accurate time-series forecasting is essential for many business scenarios such as planning, supply chain management, and resource allocation. BigQuery now embeds TimesFM, a state-of-the-art pre-trained model from Google Research, enabling powerful forecasting via the simple AI.FORECAST function.

Time-series analysis is used across a wide range of fields including retail, healthcare, finance, manufacturing, and the sciences. Through the use of forecasting algorithms, users can have a more thorough understanding of their data including the recognition of trends, seasonal variations, cyclical patterns, and stationarity. 

BigQuery already natively supports the well-known ARIMA_PLUS and ARIMA_PLUS_XREG models for time-series analysis. More recently, with the rapid progress and success of large pre-trained LLM models, the Google Research team developed TimesFM, a foundational model specifically for the time series domain.

The Time Series foundation model

TimesFM is a forecasting model that’s pre-trained on a large time-series corpus of 400 billion real-world time-points. A big advantage ...