You must locate BigQuery tables containing an employee_ssn column across 1000+ datasets and many projects with minimal effort. What should you do?

Searching Data Catalog for "employeessn" is the most efficient solution because Data Catalog is designed for discovering and managing metadata across an organization's data assets. It allows you to search for specific column names, tags, or other metadata across multiple projects and datasets with minimal effort. Writing a shell script using the bq CLI or a script that loops through projects and queries INFORMATIONSCHEMA.COLUMNS would be significantly more complex and time-consuming. These methods require custom scripting to handle project iteration, authentication, and error handling across potentially thousands of datasets, which is exactly what Data Catalog simplifies. Creating a Cloud Dataflow job is an even more complex and expensive solution for a metadata search task that Data Catalog handles natively and more efficiently.