bigquery-ai-ml

name	bigquery-ai-ml
metadata	{"category":"AiAndMachineLearning"}
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, 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, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

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.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.
  • 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.