The Scenario
It's Thursday. Your quarterly business review is Friday morning, and the product manager across from you just asked if you could pull the feature adoption events from BigQuery into a shared Excel workbook so the team can slice them before the slides are finalized. Five hundred rows. No code. No pipeline. Just the data, in the workbook, today.
The bad version:
- Open BigQuery console, find the right project and dataset, figure out which table holds the feature_events data, write a LIMIT 500 query, run it.
- Export to CSV, download it, open it in Excel — but the CSV uses commas inside fields and Excel misparses three columns. Fix the import. Copy the contents into the shared workbook. Fix the headers that came through as snake_case when the PM expected title case.
- Repeat when she asks for 600 rows instead.
That is not the hard part of your job. But it takes time, and time is what you don't have the day before a QBR.
The Easy Way: One Prompt in SheetXAI
SheetXAI lives inside your Excel workbook. It reads the workbook and talks to Google BigQuery on your behalf — you describe what you need, and the rows land.
Fetch the first 500 rows from the BigQuery table my-project.analytics.feature_events and paste them into my Excel sheet starting at row 2, using the field names as column headers
What You Get
- Row 1 gets the field names from the BigQuery table schema as column headers.
- Rows 2 through 501 get the data, in the order BigQuery returns them.
- All 500 rows land in a single write — no row-by-row polling, no partial results.
- If you need a specific sort order, you say so in the prompt and SheetXAI adjusts the query before running it.
What If the Data Is Not Quite Ready
You only want rows from a specific feature
Fetch up to 500 rows from my-project.analytics.feature_events where the feature_name is 'bulk_export', paste them into my Excel sheet starting at row 2 with field names as headers.
The table is partitioned and you want a specific date range
Fetch up to 500 rows from my-project.analytics.feature_events for events between 2026-04-01 and 2026-04-30, paste them starting at row 2 with headers, and sort by event_timestamp ascending.
You also want to know how many total rows match before pulling
First count the total rows in my-project.analytics.feature_events where feature_name = 'bulk_export', write that count into cell B1, then fetch the first 500 matching rows and paste them starting at row 3 with headers.
Pull the data, flag duplicate user_ids, and write everything in one go
Fetch the first 500 rows from my-project.analytics.feature_events, paste them into my Excel sheet starting at row 2 with headers, and in a new column called 'duplicate_user' write TRUE if that user_id appears more than once in the result, FALSE otherwise.
Combining the pull and the quality check means you only have to ask once.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook where you need a BigQuery table's contents — point it at the table, tell it how many rows and what filters apply, and get the data. For pushing data the other direction, see bulk insert rows into BigQuery from an Excel workbook or return to the Google BigQuery integration overview.