BigQuery Adds Time Series ML Functions, Deprecates Graph in Standard, and Enhances AI Agent CLI Access
BigQuery introduces new table-valued machine learning functions for time series analysis in preview, including ML.TREND, ML.SEASONALITY, and ML.DETECT_CHANGE_POINTS. These functions enable users to identify directional trajectories, repeating patterns, and structural shifts within their data. Additionally, support for core BigQuery Graph processing in the Standard edition and with on-demand billing will be deprecated starting April 26, 2027, restricting it to Enterprise editions. A new `run_bq_command` tool is also in preview, allowing AI agents to perform advanced BigQuery operations through the Cloud CLI remote MCP server.
Deprecations (1) ›
- BigQuery
Starting April 26, 2027, core graph processing for BigQuery Graph will be restricted to the BigQuery Enterprise and Enterprise Plus editions . Consequently, we are deprecating support for Standard edition and on-demand billing for core graph processing. Graph measures will remain available in the Enterprise and Enterprise Plus editions and for queries run using on-demand pricing. Measures are not available in Standard edition.
Features (2) ›
- BigQuery
BigQuery supports the following table-valued functions in the query editor and as part of conversational analytics to help you analyze your time series data: ML.TREND : identify the directional trajectory of your data. ML.SEASONALITY : identify repeating patterns in your data. ML.DETECT_CHANGE_POINTS : identify intervals where structural shifts occur in your data. These functions are in preview .
- BigQuery
The run_bq_command tool exposes the bq command-line tool within the Cloud CLI remote MCP server. AI agents can now execute advanced BigQuery operations, such as job scheduling, job management, and reservation management, through a managed MCP endpoint. For more information, see Use the Cloud CLI remote MCP server . This feature is in Preview .
https://docs.cloud.google.com/release-notes#August_20_2026
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