How to Connect BigQuery to ChatGPT with Windsor.ai

To connect Google BigQuery to ChatGPT, connect BigQuery in Windsor.ai with read-only access, add the Windsor.ai app inside ChatGPT, then ask about your tables in plain language. There is no SQL to write, no code to maintain, and no CSV exports to move around. The whole setup takes about a minute.

Once it is live, anyone on your team can ask ChatGPT questions like “what was revenue by month last year” and get an answer straight from your BigQuery data. Windsor.ai is a no-code data integration platform used by 9,000+ marketing teams to bring their data into the tools they already work in.

Why connect BigQuery to ChatGPT

• No SQL required. Ask in plain language instead of writing queries, so people who do not use SQL can still get answers from the warehouse.
• Your own data, live. ChatGPT reads from your actual BigQuery datasets and tables, not a stale spreadsheet copy.
• No code, no exports. You do not build a pipeline or download CSVs. Windsor.ai handles the connection.
• Read-only and safe. Windsor.ai reads and reports your data. It never writes back or changes anything in BigQuery.
• One place for everything. Combine BigQuery with your ad, analytics, and e-commerce sources for cross-channel reporting from a single source of truth.

Ways to connect BigQuery to ChatGPT compared

There are a few paths to get BigQuery data into ChatGPT. Here is how they compare, and why the native Windsor.ai app is the fastest for most teams.

Method	Setup time	Code needed	Best for
Windsor.ai app in ChatGPT (recommended)	About 1 minute	None	Asking questions about your BigQuery tables in plain language inside ChatGPT
Windsor.ai MCP	A few minutes	None	Bringing the same data into other MCP-ready AI assistants
No-code automation platform	Per workflow	None	Triggered record syncing between apps
API and code	Longer	Yes, engineering time	Fully custom in-house pipelines

How the connection works

Windsor.ai connects to your BigQuery account with read-only access and makes your datasets available to ChatGPT through the native Windsor.ai app. When you ask a question in ChatGPT, the app fetches the relevant rows from your tables, and ChatGPT turns them into a plain-language answer, a table, or a summary. Nothing is copied to a third place you have to manage, and nothing is written back to BigQuery. For a full overview of the native flow, see Connect BigQuery to ChatGPT native app.

How to connect BigQuery to ChatGPT in 3 steps

Step 1: Connect BigQuery in Windsor.ai

Open onboard.windsor.ai/app/big_query and sign in or create your free Windsor.ai account. Authorize BigQuery with read-only access so Windsor.ai can read your datasets and tables. You stay in control of which project and datasets are shared, and access is read-only the whole time.

Step 2: Add the Windsor.ai app in ChatGPT

Open the Windsor.ai app in ChatGPT at chatgpt.com/apps/windsor-ai, install it, sign in with the same Windsor.ai account, and pick BigQuery as your connector. It is one click, with no code and nothing to paste. If you want the detailed walkthrough with screenshots, follow how to integrate your data into ChatGPT.

Step 3: Ask in plain language

That is it. Type a question about your data and ChatGPT answers from your BigQuery tables. Start with something simple to confirm the connection, then move on to the metrics you care about. Example prompts are below.

The BigQuery data that matters

BigQuery is a data warehouse, so the data is whatever you have loaded into it. There is no fixed field list. Instead, ChatGPT works with your own projects, datasets, tables, columns, and rows. If you can query it in BigQuery, you can ask ChatGPT about it. Common examples of what teams point ChatGPT at include:

• Revenue and orders tables from your e-commerce or billing data
• Marketing spend and campaign tables pulled from your ad platforms
• Sessions, events, and conversion tables from your analytics data
• Customer and subscription tables for retention and lifetime value questions
• Any custom table your team has modeled in BigQuery

Because the connection is read-only, asking questions never changes or deletes anything in these tables.

Example prompts to try

Once BigQuery is connected, paste one of these into ChatGPT and adjust the table names to match your own schema.

Summarize total revenue by month from my orders table for the last 12 months.

Which campaigns in my marketing_spend table had the highest cost last quarter? Rank the top 10.

Compare new versus returning customer counts by week from my sessions table.

Find the top 5 products by units sold this year and show month-over-month growth.

Ready to try it? Start for free with Windsor.ai. The free forever plan needs no credit card, and paid plans start from 19 dollars per month when you need more sources and history.

Bonus: blended, cross-channel reporting

The real payoff comes when BigQuery is not the only source connected. Add your ad platforms, analytics, and e-commerce connectors in Windsor.ai, and ChatGPT can reason across all of them at once. That means blended ROAS, spend versus revenue, and full-funnel questions from a single source of truth, without stitching spreadsheets together by hand.

Join my BigQuery ad_spend table with revenue from my orders table and show blended ROAS by channel for the last 30 days.

This cross-channel reporting is where a warehouse plus ChatGPT starts to replace hours of manual data prep.

Is my BigQuery data safe?

Yes. The connection is read-only by design, so Windsor.ai reads and reports your BigQuery data but never writes back, edits, or deletes anything at the source. You authorize access through Google, you choose what is shared, and you can revoke access at any time from your Windsor.ai account. Your credentials are never pasted into the chat.

Troubleshooting

• ChatGPT cannot see my data. Confirm you are signed in to the same Windsor.ai account in both places and that BigQuery shows as connected at onboard.windsor.ai/app/big_query.
• A table is missing. Make sure the dataset that holds it was included when you authorized access, then reload the connector in the ChatGPT app.
• Answers look empty. Reference the exact table and column names from your schema in the prompt, since ChatGPT reads whatever you actually loaded into BigQuery.
• The app is not listed. Open the Windsor.ai app link again and install it, then pick BigQuery as the connector.

Connect BigQuery to other AI tools

The same read-only Windsor.ai connection works with more than ChatGPT. If your team uses Claude, follow connect BigQuery to Claude for the equivalent no-code setup. To see every source you can bring into ChatGPT alongside BigQuery, browse the ChatGPT connectors and integrations hub.

Turn your BigQuery data into answers. Start for free at Windsor.ai, connect BigQuery read-only, and ask ChatGPT your first question in about a minute.