How can a user run jobs in BigQuery without interrupting important workloads at minimal cost?

Running jobs in BigQuery as batch jobs is an effective way to manage workload and cost efficiently. Batch jobs in BigQuery are designed to execute queries and other operations during off-peak hours, which means they can be queued and executed when system resources are less utilized. This approach significantly reduces the risk of interrupting important workloads that may be running during peak times.

When jobs are run as batch, the cost can also be minimized since they can take advantage of lower demand on the system and do not require immediate execution. This allows for a more predictable cost structure, as batch jobs are processed at times conducive to resource availability, leading to potential savings during high-demand periods.

On the other hand, a separate project could lead to increased complexities in managing permissions and expenses, while adding a user with a job.role in the existing project might not ensure that important workloads remain unaffected. Allowing users to run jobs only during non-peak times might not always be feasible, especially if the workload varies. Therefore, adopting a batch processing strategy clearly stands out as the most suitable option for executing jobs without disrupting essential operations at minimal cost.