BigQuery introduces augmented analytics Table-Valued Functions for automated insights
BigQuery now offers a suite of augmented analytics Table-Valued Functions (TVFs) that use AI, ML, and statistical methods to automate complex data analysis. These six new functions, including AI.KEY_DRIVERS and ML.DETECT_CHANGE_POINTS, help diagnose metric changes, uncover trends, and quantify business impact. They run directly on BigQuery data, speeding up analysis and enabling integration with AI agents for conversational data investigation. This allows for efficient chaining of analytical steps, such as identifying change points, attributing drivers, and measuring causal effects.
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- BigQuery adds augmented analytics Table-Valued Functions
BigQuery now includes a suite of augmented analytics Table-Valued Functions (TVFs) that leverage AI, ML, and statistical methods to automate complex data analysis. Six new functions are introduced: AI.KEY_DRIVERS, AI.CAUSAL_EFFECT, ML.CORRELATION, ML.DETECT_CHANGE_POINTS, ML.TREND, and ML.SEASONALITY. These TVFs run directly on BigQuery data, enabling automated insight discovery, pattern explanation, and integration with AI agents for conversational data investigation workflows.
https://cloud.google.com/blog/products/data-analytics/bigquery-augmented-analytics-tvfs/
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