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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, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.

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  • Added November 7, 2026
ai-agentssql

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SKILL.md
---
name: bigquery-ai-ml
metadata:
  version: v1
description: >-
  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, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.
---

# 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`.

> [!IMPORTANT]
> You MUST read and follow the global constraints and mandatory function routing rules in
> [ai_function_best_practices.md](references/ai_function_best_practices.md) before writing any BQML AI/ML SQL query.

## Reference Directory

-   **Best Practices**:
    [ai_function_best_practices.md](references/ai_function_best_practices.md)

-   **Functions Reference**:

    -   **AI.AGG**: [ai_agg.md](references/ai_agg.md) - Multi-row semantic
        aggregation and summarization.
    -   **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.
    -   **VECTOR_SEARCH**:
        [vector_search.md](references/vector_search.md) - Vector search
        best practices.

Files in this skill

  • PROVENANCE.json240 B
  • SKILL.md2.8 KB
  • UPSTREAM-LICENSE.txt11.1 KB
  • references/ai_agg.md3.5 KB
  • references/ai_classify.md3.7 KB
  • references/ai_detect_anomalies.md4.5 KB
  • references/ai_evaluate.md2.2 KB
  • references/ai_forecast.md6.5 KB
  • references/ai_function_best_practices.md2.8 KB
  • references/ai_generate.md3.9 KB
  • references/ai_generate_embedding.md1.6 KB
  • references/ai_generate_table.md2.9 KB
  • references/ai_if.md2 KB
  • references/ai_key_drivers.md4 KB
  • references/ai_score.md1.9 KB
  • references/ai_search.md3.7 KB
  • references/ai_similarity.md2.7 KB
  • references/ml_contribution_analysis.md4.8 KB
  • references/remote_models.md871 B
  • references/vector_search.md4 KB

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