Automated Supply Chain Insights with AI-Powered BigQuery Analysis
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Unlock real-time supply chain intelligence by seamlessly integrating AI with your BigQuery data. This n8n workflow empowers you to ask natural language questions about your shipment data and receive instant, structured insights.
About This Workflow
This n8n workflow revolutionizes how you interact with your supply chain data by leveraging the power of AI and BigQuery. It begins with a user-friendly chat interface, allowing you to pose questions about your shipment performance in plain English. An intelligent AI agent, specifically trained as an SQL assistant for supply chain analytics, then translates your request into a precise BigQuery query. This query is executed against your transport.shipments table, and the results are returned in a clear, structured format, ready for immediate analysis. Eliminate manual query writing and complex data manipulation; get the insights you need, when you need them.
Key Features
- Natural Language Querying: Ask questions about your supply chain data using simple text.
- AI-Powered SQL Generation: An intelligent agent translates your requests into efficient BigQuery SQL queries.
- Automated Data Retrieval: Directly query your BigQuery
transport.shipmentstable without manual intervention. - Structured Data Output: Receive results formatted as tables or concise numerical summaries.
- Customizable AI Agent: Tailor the AI's behavior, rules, and schema awareness to your specific needs.
How To Use
- Setup Trigger: Configure the initial node (e.g., Chat, Telegram, Slack) to receive your data-related questions.
- Configure AI Agent:
- Use the
AI Control Tower Agentnode and connect your preferred chat model (e.g., OpenAI GPT-4o-mini). - Crucially, update the
systemMessageparameter:- Correctly specify your BigQuery table name (e.g.,
transport.shipments). - Detail the fields and their meanings within your
transport.shipmentstable. - Refine the AI's behavior and output formatting rules as needed.
- Correctly specify your BigQuery table name (e.g.,
- Use the
- Integrate Query Tool:
- Use the
Call Query Toolnode to bridge the AI Agent and your BigQuery workflow. - Ensure the
workflowIdpoints to your dedicated BigQuery execution workflow. - Configure
workflowInputsto correctly pass the AI-generatedqueryto the BigQuery tool.
- Use the
- Configure BigQuery Workflow:
- In a separate n8n workflow, add the
Query Databasenode (Google BigQuery). - Set the
sqlQueryparameter to={{ $json.query }}to dynamically receive the SQL query. - Provide your BigQuery project ID and ensure your Google Cloud credentials are set up.
- This workflow will execute the query and return the results to the
Call Query Toolnode, which then passes it back to the AI agent for presentation.
- In a separate n8n workflow, add the
Apps Used
Workflow JSON
{
"id": "0dfc9557-cc55-4369-a5e8-b4be01c9b14b",
"name": "Automated Supply Chain Insights with AI-Powered BigQuery Analysis",
"nodes": 26,
"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: 0dfc9557-cc55...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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