bigquery-ai-ml

---
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.

From googlecloudplatform/data-agent-kit-plugin at 0dd8034, shown as plain text under its license: Apache-2.0 (permissive). The license text is in LICENSE.

• SKILL.md2.9 KB · d8d93967ba92
• references/
• ai_agg.md3.6 KB · 8c48d0d0df59
• ai_classify.md3.8 KB · 372531829a6e
• ai_detect_anomalies.md4.7 KB · 60c873f1272f
• ai_evaluate.md2.2 KB · 5b195fc893ec
• ai_forecast.md6.7 KB · 818f36c1f922
• ai_function_best_practices.md2.8 KB · 546c3770d1ef
• ai_generate.md4.0 KB · cd89d035d3d3
• ai_generate_embedding.md1.7 KB · 7f8522cc9973
• ai_generate_table.md3.0 KB · 49de655028ca
• ai_if.md2.1 KB · c833954f58ca
• ai_key_drivers.md4.1 KB · 2d5eb5d30814
• ai_score.md1.9 KB · 2d473f9850d5
• ai_search.md3.8 KB · 44ab2b704113
• ai_similarity.md2.8 KB · 52f54d47c68f
• ml_contribution_analysis.md4.9 KB · e6b4d0c705b4
• remote_models.md871 B · 58f7405ab59f
• vector_search.md4.1 KB · 80c733278415

18 files, 60 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.