BigQuery · Status at source date: Newsletter archive
BigQuery adds time-series functions to the query editor
BigQuery's 20 August release notes added preview support for table-valued functions, including ML.TREND, ML.SEASONALITY, and ML.DETECT_CHANGE_POINTS in the query editor and conversational analytics. The functions are designed to expose patterns and anomalies in time-series data through reusable queries.
Why it matters for advertisers
For you, this means campaign and revenue monitoring can move closer to native warehouse analysis, so test the functions against existing anomaly-detection logic before replacing production models.
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BigQuery adds time-series functions to the query editor
BigQuery's 20 August release notes added preview support for table-valued functions, including ML.TREND, ML.SEASONALITY, and ML.DETECT_CHANGE_POINTS in the query editor and conversational analytics. The functions are designed to expose patterns and anomalies in time-series data through reusable queries. For you, this means campaign and revenue monitoring can move closer to native warehouse analysis, so test the functions against existing anomaly-detection logic before replacing production models.
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