Question

A financial analytics team stores 4 TB of transaction data in a BigQuery table. Business analysts who are comfortable with spreadsheets need to explore this data, build pivot tables, and create charts without writing SQL or exporting the data to CSV (which would exceed spreadsheet row limits and create stale copies). They also require that any drill-down reflects the current data in BigQuery. Which approach best meets these requirements?

Accepted Answer

Connect the BigQuery table to Google Sheets using Connected Sheets so analysts can build pivot tables and charts against live BigQuery data.

Answer

Schedule a daily BigQuery export of the full table to a CSV file in Cloud Storage and have analysts open it in Google Sheets.

Answer

Grant analysts the BigQuery Data Viewer role and train them to write SQL queries in the BigQuery console.

Answer

Create a materialized view on the table and have analysts query it through the bq command-line tool.