On October 9, 2026, Alteryx and Google Cloud detailed an integration between Alteryx One Live Query and Google Cloud BigQuery designed to handle unstructured data at scale. The platform links browser-based workflow authoring with BigQuery-native execution and AI models like Gemini.
Warehouse-Native Execution
According to Google Cloud and Alteryx, the integration allows business users to build data pipelines using an intuitive, browser-based environment without writing code. The system executes secure SQL pushdown directly within BigQuery, meaning transformation logic runs inside the warehouse rather than across the network.
The architecture consists of three layers: the browser authoring layer for visual workflows, Alteryx One Platform Services as the coordination layer, and Google Cloud as the governed data and execution layer. Platform services handle request coordination, execution planning, result retrieval, and workflow observability.
AI-Driven Document Extraction
The workflow handles unstructured documents such as vendor invoices staged in Google Cloud Storage. Using Alteryx tools, the system extracts structured fields with user-selected models like Gemini AI or Document AI, standardizes results, and compares them against historical records in BigQuery.
Michael Wyant, Vice President of Enterprise Data & Corporate Solutions at Papa Johns, said the integration fits naturally into the Google Cloud experience and makes analytics more accessible. The companies state that the combination increases straight-through processing, speeds up reconciliation, and reduces manual exceptions.
Key facts and where they come from
- Alteryx One Live Query and Google Cloud BigQuery integrate to execute data transformations directly within the warehouse.
Alteryx One Live Query and Google Cloud BigQuery redefine how enterprises handle complex, unstructured data at scale by reducing reliance on disconnected tools
- The document extraction step utilizes either Document AI or Gemini AI depending on workflow configuration.
The extraction step uses the user-selected model, either Document AI or Gemini AI, depending on the workflow configuration.