Question-25: You have just been let go from a large social networking firm and recruited by a new company. At the new company, there is a Google Cloud project that employs BigQuery as a pay-per-use option for data warehousing. You need to keep an eye on queries in real time in order to determine which users spend the most money and which inquiries cost the most money. What steps should you take?
A. 1. Within the BigQuery dataset, which is comprised of all of the tables that will be searched, add a label for each user who is authorised to initiate a query. 2. Navigate your browser to the project's Billing page. 3. Navigate to the Reports tab. 4. Choose BigQuery as the product, and then filter by the individual whose information you wish to see.
B. 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery. 2. Perform a BigQuery query on the generated table to extract the information you need.
C. 1. In order to export BigQuery data access logs to Cloud Storage, you must first create a sink for Cloud Logging. 2. Construct a Dataflow pipeline that can calculate the cost of searches based on the users involved.
D. 1. Start the export of billing information into BigQuery. 2. To retrieve the information you require from the billing table, run a query in BigQuery using that table's name.
Correct Answer
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: 2 Explanation: Through its Reports module and BigQuery, Google provides a means of exercising expense management and doing cost analysis. The ability to automatically export your daily consumption and expense estimations is made available to you by BigQuery. One of the most significant benefits is that you will have the ability to filter out certain projects, dates, items, and services, among other things. If you are an MSP and don't want the customer to get the BigQuery fee, you should make sure that you have an internal Project in Google that you can utilize. This will ensure that any costs will be paid to your account rather than the client's account. BigQuery does provide a free tier, however if you want more information about the many payment options, go here. In our previous work with BigQuery, the cost was around $0.4 for three months' worth of data and 46 separate projects.