Give business users a chat box; get back valid BigQuery SQL and live query results.
Give business users a chat box; get back valid BigQuery SQL and live query results. The workflow: Captures a plain-language question from a chat widget or internal portal. Fetches the current table + column schema from your BigQuery dataset (via INFORMATION_SCHEMA). Feeds both the schema and the question to GPT-4o so it can craft a syntactically correct SQL query using only fields that truly exist. Executes the AI-generated SQL in BigQuery and returns the results. Stores a short-term memory by session, enabling natural follow-up questions. Perfect for analysts, customer-success teams, or any stakeholder who needs data without writing SQL. ⚙️ Setup Instructions Import the workflow n8n → Workflows → Import from File (or Paste JSON) → Save Add credentials | Service | Where to create credentials | Node(s) to update | |---------|----------------------------|-------------------| | OpenAI | <https://platform.openai.com> → Create API key | OpenAI Chat Model | | Google BigQuery | Google Cloud Console → IAM & Admin → Service Account JSON key | Google BigQuery (schema + query) | Point the schema fetcher to your dataset In Google BigQuery1 you’ll see: SELECT table_name, column_name, data_type FROM n8nautomation-453001.email_leads_schema.INFORMATION_SCHEMA.COLUMNS Replace n8nautomation-453001.email_leads_schema with YOUR_PROJECT.YOUR_DATASET. Keep the rest of the query the same—BigQuery’s INFORMATION_SCHEMA always surfaces table_name, column_name, and data_type. Update the execution node Open Google BigQuery (the second BigQuery node). In Project ID select your project. The SQL Query field is already {{ $json.output.query }} so it will run whatever the AI returns. (Optional)Embed the chat interface Test end-to-end Open the embedded chat widget. Ask: “How many distinct email leads were created last week?” After a few seconds the workflow will return a table of results—or an error if the schema lacks the requested fields. As specific questions about your data Activate Toggle Active so the chat assistant is available 24/7. 🧩 Customization Ideas Row-limit safeguard**: automatically append LIMIT 1000 to every query. Chart rendering**: send query results to Google Sheets + Looker Studio for instant visuals. Slack bot**: forward both the question and the SQL result to a Slack channel for team visibility. Schema caching**: store the INFORMATION_SCHEMA result for 24 hours to cut BigQuery costs. Contact Email:** rbreen@ynteractive.com Website:** https://ynteractive.com YouTube:** https://www.youtube.com/@ynteractivetraining LinkedIn:** https://www.linkedin.com/in/robertbreen. An n8n automation workflow template by Robert Breen.
Robert Breen
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