AI Agent for Google BigQuery

"Run the daily transaction query in BigQuery, identify the top 5 anomalies, and draft a summary email in Gmail for the lead analyst."

"Scan the [Customer] table in BigQuery for empty fields in the email column and export the list to Google Sheets."

"Query the [Revenue] table for total growth and draft a slack message with the key findings."

"Review the last 24 hours of BigQuery logs, identify failed jobs, and list them in a Google Sheet."

"Run a query to find customers who haven't logged in for 30 days and add them to a new Google Sheet."

"Compare the schema of [Table A] and [Table B] in BigQuery and report differences."

"List all BigQuery tables older than 90 days and draft a deletion report."

"Count rows in the new [Staging] table and compare against the [Source] table."

"Calculate the total cost of queries run today and alert me if it exceeds $50."

"Find all date fields in the [Logs] table and ensure they follow YYYY-MM-DD format."

"Query BigQuery for the number of active users for [Feature X] and post to Slack."

"Analyse the [Events] table for the top 3 exit pages and summarise for the team."

"Run a query to group users by their usage frequency and export to Google Sheets."

"Search the [ErrorLogs] table for any spikes in 500 errors since 9 AM."

"Extract the top 5 KPIs from BigQuery and format them for a presentation."

"Query BigQuery for total conversions attributed to [Campaign Y] and email the result."

"Query the [Leads] table for users with high engagement scores and create a list in Google Sheets."

"Run a query to group leads by region and source, then post the summary to Slack."

"Analyse the [Traffic] table for the last 7 days and highlight the top 3 traffic sources."

"Fetch current conversion counts from BigQuery and update the [Marketing] Google Sheet."