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Bigquery AI Ml by google — Agent Skill

Name: Bigquery AI Ml
Rating: 4.2 (5 reviews)
Author: Google

Bigquery AI Ml

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

Google Updated Sep 22, 2026 14.4k repo stars

File contents

BigQuery AI & ML

BigQuery integrates with Vertex AI to provide powerful machine learning and generative AI capabilities directly within SQL queries using built-in functions like AI.FORECAST, AI.KEY_DRIVERS, AI.DETECT_ANOMALIES, and AI.GENERATE.

Reference Directory

Functions Reference:
- AI.AGG: ai_agg.md - Multi-row semantic aggregation and summarization.
- AI.CAUSAL_EFFECT: ai_causal_effect.md - Quantifies the impact of an intervention on a time series.
- AI.CLASSIFY: ai_classify.md - Classify text.
- AI.DETECT_ANOMALIES: ai_detect_anomalies.md - Detect anomalies.
- AI.EVALUATE: ai_evaluate.md - Evaluate models.
- AI.FORECAST: ai_forecast.md - Time-series forecasting.
- AI.GENERATE: ai_generate.md - Generate text using LLMs.
- AI.GENERATE_EMBEDDING: ai_generate_embedding.md - Generate embeddings.
- AI.GENERATE_TABLE: ai_generate_table.md - Table-valued AI generation.
- AI.IF: ai_if.md - Evaluate semantic conditions.
- AI.KEY_DRIVERS: ai_key_drivers.md - Identifies key drivers, this is a TVF.
- AI.SCORE: ai_score.md - Score data.
- AI.SEARCH: ai_search.md - Semantic search.
- AI.SIMILARITY: ai_similarity.md - Semantic similarity.
- Remote Models: remote_models.md - Working with remote models (Vertex AI).
- CONTRIBUTION_ANALYSIS: ml_contribution_analysis.md
  - Finds contributing factors, key drivers of change. Requires creating a MODEL entity.
- ML.CORRELATION: ml_correlation.md - Calculates correlation between columns, optionally sliced by dimensions.
- ML.DETECT_CHANGE_POINTS: ml_detect_change_points.md - Detects structural breaks or sustained shifts in a time series.
- ML.SEASONALITY: ml_seasonality.md - Extracts seasonal components from a time series.
- ML.TREND: ml_trend.md - Extracts the long-term trend component from a time series.
- VECTOR_SEARCH: vector_search.md - Vector search best practices.

Related Skills

BigQuery Basics Skill: SKILL.md file for core BigQuery concepts, resource management, CLI, and client libraries.

---name: bigquery-ai-ml-2description: Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.---# BigQuery AI & MLBigQuery integrates with Vertex AI to provide powerful machine learning andgenerative AI capabilities directly within SQL queries using built-in functionslike `AI.FORECAST`, `AI.KEY_DRIVERS`, `AI.DETECT_ANOMALIES`, and `AI.GENERATE`.## Reference Directory- **Functions Reference**: - **AI.AGG**: [ai_agg.md](references/ai_agg.md) - Multi-row semantic aggregation and summarization. - **AI.CAUSAL_EFFECT**: [ai_causal_effect.md](references/ai_causal_effect.md) - Quantifies the impact of an intervention on a time series. - **AI.CLASSIFY**: [ai_classify.md](references/ai_classify.md) - Classify text. - **AI.DETECT_ANOMALIES**: [ai_detect_anomalies.md](references/ai_detect_anomalies.md) - Detect anomalies. - **AI.EVALUATE**: [ai_evaluate.md](references/ai_evaluate.md) - Evaluate models. - **AI.FORECAST**: [ai_forecast.md](references/ai_forecast.md) - Time-series forecasting. - **AI.GENERATE**: [ai_generate.md](references/ai_generate.md) - Generate text using LLMs. - **AI.GENERATE_EMBEDDING**: [ai_generate_embedding.md](references/ai_generate_embedding.md) - Generate embeddings. - **AI.GENERATE_TABLE**: [ai_generate_table.md](references/ai_generate_table.md) - Table-valued AI generation. - **AI.IF**: [ai_if.md](references/ai_if.md) - Evaluate semantic conditions. - **AI.KEY_DRIVERS**: [ai_key_drivers.md](references/ai_key_drivers.md) - Identifies key drivers, this is a TVF. - **AI.SCORE**: [ai_score.md](references/ai_score.md) - Score data. - **AI.SEARCH**: [ai_search.md](references/ai_search.md) - Semantic search. - **AI.SIMILARITY**: [ai_similarity.md](references/ai_similarity.md) - Semantic similarity. - **Remote Models**: [remote_models.md](references/remote_models.md) - Working with remote models (Vertex AI). - **CONTRIBUTION_ANALYSIS**: [ml_contribution_analysis.md](references/ml_contribution_analysis.md) - Finds contributing factors, key drivers of change. Requires creating a MODEL entity. - **ML.CORRELATION**: [ml_correlation.md](references/ml_correlation.md) - Calculates correlation between columns, optionally sliced by dimensions. - **ML.DETECT_CHANGE_POINTS**: [ml_detect_change_points.md](references/ml_detect_change_points.md) - Detects structural breaks or sustained shifts in a time series. - **ML.SEASONALITY**: [ml_seasonality.md](references/ml_seasonality.md) - Extracts seasonal components from a time series. - **ML.TREND**: [ml_trend.md](references/ml_trend.md) - Extracts the long-term trend component from a time series. - **VECTOR_SEARCH**: [vector_search.md](references/vector_search.md) - Vector search best practices.## Related Skills- [BigQuery Basics Skill](../bigquery-basics): SKILL.md file for core BigQuery concepts, resource management, CLI, and client libraries.

Frequently asked questions