Google BigQuery Agent
Analyze massive datasets in BigQuery using natural conversation, not SQL.
What it does
The BigQuery agent makes your entire Google Cloud data warehouse accessible through conversation. From multi-terabyte analytical queries to real-time streaming data, your team can ask questions and get results without knowing BigQuery SQL dialects, partitioning strategies, or clustering configurations. The agent handles slot management, cost optimization, and result caching automatically.
Why a supervised agent — not a raw connector?
Key Capabilities
How It Works
Connect
Authenticate with your Google Cloud project. The agent discovers datasets, tables, and access policies.
Configure
Set billing limits, define accessible projects, and specify data sensitivity levels.
Ask
Ask questions through the Personal Assistant. The agent writes cost-efficient queries with automatic dry-run estimates.
Improve
Learns your schema conventions, common aggregations, and team-specific terminology over time.
Use Cases
Marketing teams analyzing campaign performance across petabytes of event data
Data teams monitoring BigQuery costs and optimizing slot utilization
Product managers querying user behavior data without SQL
Executives requesting real-time KPI dashboards on demand
Invoked from your Personal AI Assistant
Users never interact with this agent directly. They ask a question through their Personal AI Assistant, and xpander routes it to the Google BigQuery agent automatically. The specialized agent handles execution within its constrained surface — validated, auditable, and isolated from every other system. One question in, structured answer out.