AI-Powered Supply Chain Analytics with BigQuery
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Leverage the power of AI to instantly query and analyze your supply chain data stored in BigQuery. This n8n workflow provides an intelligent assistant to extract actionable insights without writing SQL.
About This Workflow
Unlock the full potential of your supply chain data with this n8n workflow. It seamlessly integrates a sophisticated AI agent with Google BigQuery, allowing you to ask natural language questions about your shipment performance and receive structured, insightful answers. The AI agent is specifically trained to understand supply chain terminology and your BigQuery schema, acting as your dedicated analyst. It intelligently constructs and executes SQL queries, returning only the essential data in a clear, tabular, or summary format. This eliminates the need for manual data extraction and SQL expertise, empowering faster, data-driven decision-making.
Key Features
- Natural Language Querying: Ask questions about your supply chain in plain English, not SQL.
- AI-Powered SQL Generation: The AI agent automatically translates your questions into BigQuery-compatible SQL queries.
- BigQuery Integration: Directly connects to your BigQuery data for real-time analysis.
- Structured Data Output: Receives results in a clean, easy-to-understand format (tables, summaries).
- Role-Specific AI Assistant: Configured as a specialized supply chain analytics expert.
How To Use
- Set up the AI Chat Model: Configure your chosen chat model (e.g., OpenAI GPT-4o-mini) with your API credentials in the 'OpenAI Chat Model' node.
- Configure the AI Agent: In the 'AI Control Tower Agent' node, update the
systemMessagewith your BigQuery table name (e.g.,transport.shipments) and adjust the field explanations to match your schema. - Integrate the BigQuery Tool: Ensure the 'Call Query Tool' node is correctly configured to point to your BigQuery tool workflow. The
workflowIdshould reference your separate BigQuery execution workflow. - Set up the BigQuery Node: In a dedicated BigQuery workflow, configure the 'Query Database' node with your Google Cloud Project ID and ensure the
sqlQueryparameter correctly receives the query from the AI agent (e.g.,={{ $json.query }}). - Connect and Test: Link the nodes as shown in the workflow and test by interacting with the AI agent through its trigger.
Apps Used
Workflow JSON
{
"id": "8a20f732-7e79-4360-b239-e655b6227beb",
"name": "AI-Powered Supply Chain Analytics with BigQuery",
"nodes": 13,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 8a20f732-7e79...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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