Google Cloud Professional Data Engineer Exam

What strategy should you implement to reduce effort for analysts running complex queries in BigQuery?

1. Create a dataset with the data that is frequently queried.

2. Create a view of the frequently queried data.

3. Export the frequently queried data into a new table.

4. Export the frequently queried data into Cloud SQL.

The correct answer is: Create a view of the frequently queried data.

Implementing a view of the frequently queried data in BigQuery is a beneficial strategy for several reasons. Views allow analysts to run complex queries more easily by encapsulating the logic of those queries within the view itself. This means that the analysts do not need to understand the intricacies of the underlying data schema or constructs, thereby reducing the cognitive load on them. Using views also helps maintain a level of abstraction, which can enhance security and enforce data governance, as you can control access to sensitive data while still allowing analysts to perform their queries. Additionally, views can simplify the query structure, making it easier to manage and modify over time without requiring changes on the analyst's end. Moreover, views are updatable in the sense that any modifications to the underlying data are immediately reflected when the view is queried, ensuring that analysts are always working with the most current data without the need to refresh or recreate tables. In contrast, creating a dataset with frequently queried data does not inherently simplify the complexity of the queries themselves; it merely organizes the data. Exporting data into a new table or into Cloud SQL could involve additional maintenance and data management overhead, as it may require handling synchronization and potential data duplication issues. Hence, a view is a more elegant solution that optim