Question-17: Google BigQuery is a cloud-based architecture that delivers outstanding performance as a result of its capacity to auto-scale up and down depending on the amount of data load and fast execute data analysis. This is made possible by Google's use of the Kubernetes distributed computing system. On the other hand, SQL Server employs a client-server architecture and, unless the user explicitly scales it, it keeps the system's performance at a consistent level throughout. Unless the user does this, however, the user may experience intermittent slowdowns. Your BigQuery project currently has participation from a number of different individuals. For auditing purposes, you need to be able to see how many inquiries were carried out by each user over the course of the previous month. What is it that you should be doing, exactly?
A. Establish a connection between Google Data Studio and BigQuery. Establish a parameter for the number of users and a metric for the length of the line.
B. To obtain the necessary information, you must first run a query on the JOBS table using the BigQuery interface.
C. To display a list of all jobs, type bq show. Use the command bq ls to list job information and obtain the necessary information for each job.
D. You can view Cloud Audit Logs by using the Cloud Audit Logging service, and then you can get the information you need by adding a filter to the query operation.

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