Google Cloud Professional Cloud Security Engineer Practice Exam

To optimize Cloud DLP usage in BigQuery, which resources' cost should be limited?

1. Compute costs and storage costs

2. Data transfer costs

3. rowsLimit and bytesLimitPerFile

4. API request costs

The correct answer is: rowsLimit and bytesLimitPerFile

To optimize Cloud Data Loss Prevention (DLP) usage in BigQuery, focusing on the rowsLimit and bytesLimitPerFile is essential because these parameters directly affect the efficiency and cost-effectiveness of DLP jobs. Setting these limits allows you to manage the amount of data scanned and processed during DLP operations. When rowsLimit is applied, it restricts the number of rows that the DLP can examine, which helps in controlling the costs associated with DLP operations, especially if you are working with large datasets. Similarly, defining bytesLimitPerFile ensures that an upper cap is set on the size of files processed at once, which can further control costs and also optimize performance by preventing the processing of excessively large files that may not yield significant additional insights. Considering the other options, while compute costs and storage costs are important in Cloud computing, they are not as directly correlated with the DLP scanning process itself. Similarly, data transfer costs pertain to moving data across services and could be a consideration in some scenarios, but they do not specifically relate to the optimization of DLP operations in BigQuery. Lastly, while API request costs can be a factor in overall project costs, they are more incidental compared to the control provided through fine-tuning the