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Viewing questions 21-30 out of questions
Questions # 21:

Your team uses Google Sheets to track budget data that is updated daily. The team wants to compare budget data against actual cost data, which is stored in a BigQuery table. You need to create a solution that calculates the difference between each day's budget and actual costs. You want to ensure that your team has access to daily-updated results in Google Sheets. What should you do?

Options:

A.

Create a BigQuery external table by using the Drive URI of the Google sheet, and join the actual cost table with it. Save the joined table as a CSV file and open the file in Google Sheets.

B.

Download the budget data as a CSV file and upload the CSV file to a Cloud Storage bucket. Create a new BigQuery table from Cloud Storage, and join the actual cost table with it. Open the joined BigQuery table by using Connected Sheets.

C.

Download the budget data as a CSV file, and upload the CSV file to create a new BigQuery table. Join the actual cost table with the new BigQuery table, and save the results as a CSV file. Open the CSV file in Google Sheets.

D.

Create a BigQuery external table by using the Drive URI of the Google sheet, and join the actual cost table with it. Save the joined table, and open it by using Connected Sheets.

Questions # 22:

Your organization plans to move their on-premises environment to Google Cloud. Your organization’s network bandwidth is less than 1 Gbps. You need to move over 500 ТВ of data to Cloud Storage securely, and only have a few days to move the data. What should you do?

Options:

A.

Request multiple Transfer Appliances, copy the data to the appliances, and ship the appliances back to Google Cloud to upload the data to Cloud Storage.

B.

Connect to Google Cloud using VPN. Use Storage Transfer Service to move the data to Cloud Storage.

C.

Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.

D.

Connect to Google Cloud using Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.

Questions # 23:

You used BigQuery ML to build a customer purchase propensity model six months ago. You want to compare the current serving data with the historical serving data to determine whether you need to retrain the model. What should you do?

Options:

A.

Compare the two different models.

B.

Evaluate the data skewness.

C.

Evaluate data drift.

D.

Compare the confusion matrix.

Questions # 24:

You have a Cloud SQL for PostgreSQL database that stores sensitive historical financial data. You need to ensure that the data is uncorrupted and recoverable in the event that the primary region is destroyed. The data is valuable, so you need to prioritize recovery point objective (RPO) over recovery time objective (RTO). You want to recommend a solution that minimizes latency for primary read and write operations. What should you do?

Options:

A.

Configure the Cloud SQL for PostgreSQL instance for multi-region backup locations.

B.

Configure the Cloud SQL for PostgreSQL instance for regional availability (HA). Back up the Cloud SQL for PostgreSQL database hourly to a Cloud Storage bucket in a different region.

C.

Configure the Cloud SQL for PostgreSQL instance for regional availability (HA) with synchronousreplication to a secondary instance in a different zone.

D.

Configure the Cloud SQL for PostgreSQL instance for regional availability (HA) with asynchronous replication to a secondary instance in a different region.

Questions # 25:

You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days. What should you do?

Options:

A.

Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.

B.

Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.

C.

Develop a batch process using Dataflow that runs weekly and deletes files based on their age.

D.

Create a Cloud Run function that runs daily and deletes files older than seven days.

Questions # 26:

Your organization sends IoT event data to a Pub/Sub topic. Subscriber applications read and perform transformations on the messages before storing them in the data warehouse. During particularly busy times when more data is being written to the topic, you notice that the subscriber applications are not acknowledging messages within the deadline. You need to modify your pipeline to handle these activity spikes and continue to process the messages. What should you do?

Options:

A.

Retry messages until they are acknowledged.

B Implement flow control on the subscribers

B.

Forward unacknowledged messages to a dead-letter topic.

C.

Seek back to the last acknowledged message.

Questions # 27:

Your team uses the Google Ads platform to visualize metrics. You want to export the data to BigQuery to get more granular insights. You need to execute a one-time transfer of historical data and automatically update data daily. You want a solution that is low-code, serverless, and requires minimal maintenance. What should you do?

Options:

A.

Export the historical data to BigQuery by using BigQuery Data Transfer Service. Use Cloud Composer for daily automation.

B.

Export the historical data to Cloud Storage by using Storage Transfer Service. Use Pub/Sub to trigger a Dataflow template that loads data for daily automation.

C.

Export the historical data as a CSV file. Import the file into BigQuery for analysis. Use Cloud Composer for daily automation.

D.

Export the historical data to BigQuery by using BigQuery Data Transfer Service. Use BigQuery Data Transfer Service for daily automation.

Questions # 28:

Your organization needs to store historical customer order data. The data will only be accessed once a month for analysis and must be readily available within a few seconds when it is accessed. You need to choose a storage class that minimizes storage costs while ensuring that the data can be retrieved quickly. What should you do?

Options:

A.

Store the data in Cloud Storaqe usinq Nearline storaqe.

B.

Store the data in Cloud Storaqe usinq Coldline storaqe.

C.

Store the data in Cloud Storage using Standard storage.

D.

Store the data in Cloud Storage using Archive storage.

Questions # 29:

Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards. You need to implement a solution quickly and efficiently. What should you do?

Options:

A.

Apply a filter to only show products with a positive profit margin.

B.

Define a new measure that calculates the profit margin by using the existing revenue and cost fields.

C.

Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).

D.

Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.

Questions # 30:

You work for a financial organization that stores transaction data in BigQuery. Your organization has a regulatory requirement to retain data for a minimum of seven years for auditing purposes. You need to ensure that the data is retained for seven years using an efficient and cost-optimized approach. What should you do?

Options:

A.

Create a partition by transaction date, and set the partition expiration policy to seven years.

B.

Set the table-level retention policy in BigQuery to seven years.

C.

Set the dataset-level retention policy in BigQuery to seven years.

D.

Export the BigQuery tables to Cloud Storage daily, and enforce a lifecycle management policy that has a seven-year retention rule.

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