A BigQuery dataset contains customers' street addresses. You need to find all occurrences of street addresses in the dataset. What should you do?

The correct answer is to create a deep inspection job on each table in your dataset with Cloud Data Loss Prevention (DLP) and an inspection template that includes the STREETADDRESS infoType. Cloud DLP is specifically designed to identify, classify, and protect sensitive data, including street addresses, across various data sources. Its STREETADDRESS infoType uses advanced detection techniques beyond simple keyword matching to accurately identify addresses. Writing a SQL query with REGEXPCONTAINS for the word "street" is insufficient because it would miss many valid addresses (e.g., "avenue," "road," or addresses without the word "street") and incorrectly flag non-address data containing "street." Creating a discovery scan configuration on your organization is for broader data discovery across multiple services, not for detailed inspection within specific BigQuery tables for a particular infoType. Creating a de-identification job is for transforming or masking sensitive data after it has been identified, not for the initial identification process itself.