Exam Professional Cloud Architect topic 1 question 187 discussion

I choose B because of "real-time". Otherwise, D seems to be the most relevant and flexible.

B is the correct answer https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring A is incorrect as there is not billing page for a project, its billing account that handles all org billing.

Google recommends to export cloud billing data to bigquery to control cost in real-time: https://cloud.google.com/billing/docs/how-to/export-data-bigquery

B is correct!

B is the correct option. Why not A: While the Billing page offers reports with user-level cost breakdowns, it doesn't provide real-time information or detailed query data. Why not D: Billing export can provide cost data in BigQuery, but it doesn't capture details about individual queries or users, making it insufficient for the specific needs of identifying costly queries and high-spending users.

b -> real time

I tend to agree with the GPT4 summary: In summary, Option B is more focused on analyzing specific BigQuery usage patterns and costs down to the level of individual queries and users. It's better for real-time analysis of query activities. Option D, on the other hand, provides a broader overview of all costs associated with the Google Cloud project, which is beneficial for general cost management but less so for in-depth analysis of specific BigQuery queries and user activities. For the specific need to discover the most costly queries and which users are responsible, Option B is more targeted and appropriate

I took PCA exam today and I passed PCA exam. In my test, I choose D on this question.

It can't be better explained https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring

B: because of" https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring And because https://cloud.google.com/billing/docs/how-to/export-data-bigquery#example-queries. is not mentioning anything about query per user. B

B don't provide the cost

The answer is D. 1. Activate billing export into BigQuery. 2. Perform a BigQuery query on the billing table to extract the information you need. Explanation: A. This option is not correct because adding a label for each user in the BigQuery dataset will not allow you to monitor the cost of queries or find out which users spend the most. B. This option is not correct because BigQuery data access logs do not include billing information or query costs. C. This option is not correct because BigQuery data access logs stored in Cloud Storage do not include billing information or query costs, and developing a Dataflow pipeline to compute the cost of queries would be unnecessarily complex. D. This is the correct option because activating billing export into BigQuery will allow you to query the billing data in real-time to discover the most costly queries and which users spend the most.

D is the easiest

1. Activate billing export into BigQuery. 2. Perform a BigQuery query on the billing table to extract the information you need.

both B and D do not meet the exact requirements while B does not give the cost D does not provide user level details. Answer A seems to better suited though complicated

For me, most simple and also available in real time is D

Option D might seem like a reasonable choice, but it doesn't provide real-time monitoring of queries, which is the requirement mentioned in the question. Activating billing export to BigQuery provides detailed billing information for your Google Cloud project. However, this method doesn't provide real-time insights into query costs and user expenditures, as billing data is typically updated once per day. On the other hand, option B allows you to monitor queries in real-time by exporting BigQuery data access logs directly to another BigQuery table, enabling you to analyze the most costly queries and user expenses as they happen.