BigQuery: Fuel your warehouse with enterprise data
BigQuery is Google Cloud’s serverless data warehouse for running SQL across datasets and tables at scale. With Tray, you can move data from CRM, ERP, marketing platforms, and internal systems into BigQuery, transform it in-flight, and orchestrate governed workflows that activate trusted warehouse data across the business.
Agents
Integrations
Automations
Use cases
BigQuery + Tray
BigQuery is where analytics models, usage data, forecasts, and financial rollups are stored across datasets and tables. But the actions tied to those insights often depend on work happening in other systems.
Tray extends BigQuery across your stack, connecting it to CRM, finance, support, marketing, and any other system you rely on. SQL queries, table updates, and dataset outputs can trigger orchestrated workflows, governed automations, and agents that take action across tools while keeping BigQuery as the analytics source of truth.
See how different teams use Tray to take action from BigQuery.
What you can do with Tray
Revenue operations
Revenue operations
If you work in revenue operations, these are common ways teams use Tray with BigQuery to turn forecasting models and pipeline analytics into coordinated action.
- Sync forecast models to CRM: Run SQL against revenue tables and write modeled outputs back to opportunities or accounts
- Trigger follow-ups from risk signals: Detect churn or expansion indicators in warehouse datasets and create tasks automatically
- Reconcile pipeline data: Compare CRM pipeline records to BigQuery tables and flag mismatches for review
Finance
Finance
If you work in finance, these are common ways teams use Tray with BigQuery to operationalize revenue models and reconciliation logic.
- Reconcile transaction tables: Compare ledger extracts in BigQuery with billing or ERP records and route discrepancies
- Trigger billing updates from revenue models: Run SQL checks against subscription or ARR tables and initiate downstream workflows
- Distribute close summaries: Generate reports from query results and send them to stakeholders automatically
Data and analytics
Data and analytics
If you work in data or analytics, these are common ways teams use Tray with BigQuery to move beyond dashboards and activate SQL outputs safely.
- Operationalize warehouse models: Run governed queries on datasets and route results into production systems
- Standardize table updates: Insert structured rows into reporting tables with validation and logging
- Expose approved queries as tools: Turn trusted SQL queries into governed tools agents or workflows can invoke
Marketing ops
Marketing ops
If you work in marketing ops, these are common ways teams use Tray with BigQuery to activate attribution and segmentation models.
- Sync attribution results to CRM: Write campaign influence or scoring outputs from warehouse tables back to records
- Export audience segments: Query segmentation tables and push audiences to ad or email platforms
- Alert on performance thresholds: Run scheduled SQL checks and notify teams when metrics cross defined limits
Support
Support
If you work in support or customer operations, these are common ways teams use Tray with BigQuery to act on usage and health signals.
- Open tickets from churn-risk tables: Query risk scores and create tickets when thresholds are met
- Sync usage metrics to CS tools: Push product usage data from BigQuery into customer success platforms
- Alert on SLA breaches: Run SQL checks against SLA tables and notify account owners with context
IT
IT
If you work in IT or security, these are common ways teams use Tray with BigQuery to operationalize audit and access data.
- Monitor audit datasets: Query access logs and trigger reviews when anomalies appear
- Reconcile identity exports: Compare IdP exports with warehouse tables and flag mismatches
- Post compliance digests: Generate scheduled summaries from audit tables and distribute them automatically
Agents
Build agents with BigQuery and Tray
Agents sit on top of your BigQuery integrations and automations. They use scoped datasets via configured credentials, call governed SQL tools, and translate warehouse insight into coordinated action across systems when required.
Give agents only the warehouse context they need
- Dataset scope: Access is limited by the IAM permissions of your configured credentials
- Schema-aligned retrieval: Retrieve results consistent with existing table schemas
- Execute live SQL queries: Run queries against BigQuery when invoked
- Project isolation: Separate connections for staging and production environments
Integrations
Integrations with BigQuery and Tray
Tray connects CRM, ERP, marketing, finance, and internal systems to BigQuery, moving structured and event data into the warehouse, and enabling governed workflows when warehouse outputs need to flow back into production systems. BigQuery remains the central analytics engine and Tray orchestrates the movement and coordination around it.
BigQuery integration capabilities
Connect BigQuery to 700+ applications and data sources, moving data into the warehouse or orchestrating governed actions from approved SQL outputs. These capabilities map directly to BigQuery’s REST resources, including datasets, tables, and jobs.
Run SQL and orchestrate BigQuery jobs across workflows
- Run Standard SQL queries: Execute queries as BigQuery jobs within approved projects and datasets
- Transform data in-flight: Join, filter, and reshape data within workflows before executing or loading in BigQuery
- Capture job responses: Retrieve job IDs and API responses within workflow logs
- Execution follows IAM scope: Queries respect the access permissions of your configured credentials
Automations
Automations with BigQuery and Tray
Use scheduled query execution, SQL Transformer steps, or workflow-driven SQL checks to manage warehouse data pipelines and, where appropriate, trigger governed downstream actions. Transform, deduplicate, or join data in-flight before writing to BigQuery or routing approved outcomes to CRM records, tickets, billing systems, or collaboration tools.
Frequently Asked Questions
Find answers to common questions about our products and services.
How does Tray authenticate to BigQuery?
Tray supports OAuth and service account JSON authentication. Scope service accounts to approved projects and datasets for least privilege access.
Can workflows start automatically?
Workflows can run on schedule or execute SQL checks within broader automation logic to detect changes in tables.
Does Tray support Standard SQL?
Yes. Tray supports Standard SQL, which is BigQuery’s default. Legacy SQL is supported only if explicitly enabled in your query configuration.
How are row inserts handled?
Row inserts use BigQuery’s streaming behavior. Streaming inserts may appear in a temporary buffer before becoming available for certain query types or DML operations.
How do we separate environments?
Use distinct connections for development and production projects, each with its own scoped credentials.
Can Tray transform data before loading it into BigQuery?
Yes. Use Tray SQL Transformer within workflows to join, filter, and reshape data before writing to BigQuery tables or triggering downstream systems.
FAQs
Workflows can run on schedule or execute SQL checks within broader automation logic to detect changes in tables.
What comes standard with Tray
Whether your systems, data, or models run in the cloud or on-premises, Tray connects them in one secure platform. Every connection, workflow, and agent operates under IT governance with encryption, audit logging, and access controls built in. Security teams can trust that all integrations comply with enterprise network and authentication policies.
Universal connectivity
- Prebuilt connectors: 700+ connectors plus a universal HTTP connector for any REST API
- Custom connectors: Build custom connectors that behave like native ones
- Connect anywhere: Cloud or on-prem systems supported
On-premises connectivity
- Connect securely: Access on-premises systems, whether first-party or third-party
- Meet network requirements: Connect through approved configurations that align with enterprise security policies
- Enterprise protocols: Support multiple on-premises security standards for safe integration
Authentication management
- Secure credentials: Collect and store authentications with full encryption
- Encrypted data: Protect all data at rest and in transit
- Role-based control: Partition credentials by workspace and access level
Security and governance
- Certified compliance: SOC 2 Type II, GDPR, CCPA, HIPAA
- End-to-end protection: Encryption, detailed audit logs, scoped connections, and OAuth scopes