Exam Associate Cloud Engineer topic 1 question 17 discussion

Solving this by first eliminating the options that don't suit us. By breaking down the question into the key requirements- 1. Analyzing Google Cloud Platform service costs from three separate projects. 2. Using standard query syntax. -> (Relational data and SQL) A. 'Cloud Storage bucket'........'Cloud Bigtable'. Not feasible, mainly because cloud BigTable is not good for Structured Data (or Relational Data on which we can run SQL queries as per the question's requirements). BigTable is better suited for Semi Structured data and NoSQL data. B. 'Cloud Storage bucket'.....'Google Sheets'. Not Feasible because there is no use of SQL in this option, which is one of the requirements. C. Local file, external tools... this is automatically eliminated because the operation we need is simple, and there has to be a GCP native solution for this. We shouldn't need to rely on going out of the cloud for such a simple thing. D. 'BigQuery'.....'SQL queries' -> This is the right answer.

Agreed, BigQuery

You need a scalable and efficient way to query cost data across multiple projects. BigQuery is the best choice because it supports large-scale data analysis using SQL. BigQuery allows you to run time-based SQL queries to analyze trends and forecast future costs. ou can write queries using window functions (e.g., DATE_TRUNC(), INTERVAL) to break costs down by day or month.

Try it here: https://lookerstudio.google.com/reporting/0B7GT7ZlyzUmCZHFhNDlKVENHYmc/page/tLtE

The correct answer is D

D is the Answer

The correct answer is D. BigQuery is a fully-managed, petabyte-scale analytics data warehouse that enables businesses to analyze all their data very quickly. It is also a good choice for analyzing cost data because it can handle large amounts of data and can perform complex queries quickly. Time window-based SQL queries allow you to analyze data over a specific time period. For example, you could write a query to calculate the total cost of a particular service for each day of the month. Here is an example of a BigQuery query that you could use to calculate the total cost of a particular service for each day of the month: sql SELECT cost, DATE(usage_start_time) AS date FROM `[PROJECT_ID].billing.dataset` WHERE service_id = 'YOUR_SERVICE_ID' GROUP BY date ORDER BY date This query will return a table with two columns: `cost` and `date`. The `cost` column will contain the total cost of the service for each day of the month. The `date` column will contain the date for each row.

yes D, is the correct answer, because we only use bigquery for semi or structured data

In GCP, Always use Big Query to export Billing. And Big Query is best for Analyzing

Big Query will allow sql analysis

The correct answer is Option D. Exporting the bill to a BigQuery dataset allows you to use SQL queries to analyze the data and create service cost estimates by service type, daily and monthly, for the next six months. This is an efficient and effective way to analyze the data, especially if you are familiar with SQL syntax. Option A, importing the bill into Cloud Bigtable, may be more complex and may not offer the same level of flexibility as using SQL queries in BigQuery. Option B, importing the bill into Google Sheets, may be more suitable for simple analysis, but may not be as efficient for more complex analysis. Option C, exporting the transactions to a local file and using a desktop tool, may not be as efficient or effective as using a cloud-based solution like BigQuery. https://cloud.google.com/billing/docs/how-to/export-data-bigquery https://cloud.google.com/bigquery/docs/reference/standard-sql/

Agreed, BigQuery

D, using standard query syntax so use BQ

Agreed, BigQuery Ans: D

Answer is D

D is the right answer.

I agreed, BigQuery Answer D is correct