What is a common drawback of using Copy jobs for frequently changing data in BigQuery?

Using Copy jobs in BigQuery for frequently changing data can lead to inaccurate results due to the fact that these jobs create a static snapshot of the data at a specific point in time. When data is frequently updated or modified, relying on a Copy job may result in a situation where the analysis reflects older information instead of the current state of the dataset. This time discrepancy can skew results, as the analytics might not take into account the latest updates, deletions, or additions that occurred after the copy was made.

In environments where data changes rapidly, using a Copy job can mislead decision-making processes, as stakeholders may analyze stale data leading to incorrect conclusions or strategies based on the analysis. Therefore, for dynamic datasets, alternative methods that accommodate real-time updates—such as streaming data ingestion or using views—are often preferred to ensure accuracy and consistency in analytics.