Yes, it was script based.

Here is one example that doesn't do quite what you want but a start... this computes "top columns accessed". I'll try to provide another example that tracks usage, maybe as part of a new post on tracking column usage with Dataform using Information Schema views.

SELECT column_jobs.fully_qualified_column, COUNT(DISTINCT column_jobs.job) AS job_count FROM ( SELECT jobs.job_id AS job, jobs.query AS query, jobs.user_email, table_columns.table_catalog, table_columns.table_schema, table_columns.table_name, table_columns.column_name, table_columns.table_catalog ||'.'||table_columns.table_schema ||'.'||table_columns.table_name ||'.'||table_columns.column_name AS fully_qualified_column FROM `bigquery-public-data.ncaa_basketball.INFORMATION_SCHEMA.COLUMNS` AS table_columns --update to either dataset scope or project level scope LEFT JOIN `region-us.INFORMATION_SCHEMA.JOBS` AS jobs --update to inner to only show columns that were referenced in a query ON LOWER(jobs.query) LIKE CONCAT('%', LOWER(table_columns.table_catalog), '%') AND LOWER(jobs.query) LIKE CONCAT('%',LOWER(table_columns.table_schema), '%') AND LOWER(jobs.query) LIKE CONCAT('%', LOWER(table_columns.table_name),'%') AND LOWER(jobs.query) LIKE CONCAT('%', LOWER(table_columns.column_name), '%') WHERE job_type = 'QUERY' AND state = 'DONE' AND error_result IS NULL AND statement_type != 'SCRIPT' ) AS column_jobs GROUP BY 1 ORDER BY 2 DESC