ADP 試験問題を無料オンラインアクセス

Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

• A.Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
• B.Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
• C.Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
• D.Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.

Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?

• A.Create a saved query in the BigQuery console that uses the SUM() function and the DATE_SUB() function. Re-run the saved query every month, and save the results to a BigQuery table.
• B.Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
• C.Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
• D.Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.

Your company uses Looker to generate and share reports with various stakeholders. You have a complex dashboard with several visualizations that needs to be delivered to specific stakeholders on a recurring basis, with customized filters applied for each recipient. You need an efficient and scalable solution to automate the delivery of this customized dashboard. You want to follow the Google- recommended approach. What should you do?

• A.Create a script using the Looker Python SDK, and configure user attribute filter values. Generate a new scheduled plan for each stakeholder.
• B.Create a separate LookML model for each stakeholder with predefined filters, and schedule the dashboards using the Looker Scheduler.
• C.Embed the Looker dashboard in a custom web application, and use the application's scheduling features to send the report with personalized filters.
• D.Use the Looker Scheduler with a user attribute filter on the dashboard, and send the dashboard with personalized filters to each stakeholder based on their attributes.

You need to create a weekly aggregated sales report based on a large volume of data. You want to use Python to design an efficient process for generating this report. What should you do?

• A.Create a Dataflow directed acyclic graph (DAG) coded in Python. Use Cloud Scheduler to schedule the code to run once a week.
• B.Create a Cloud Run function that uses NumPy. Use Cloud Scheduler to schedule the function to run once a week.
• C.Create a Cloud Data Fusion and Wrangler flow. Schedule the flow to run once a week.
• D.Create a Colab Enterprise notebook and use the bigframes.pandas library. Schedule the notebook to execute once a week.

You need to design a data pipeline that ingests data from CSV, Avro, and Parquet files into Cloud Storage.
The data includes raw user input. You need to remove all malicious SQL injections before storing the data in BigQuery. Which data manipulation methodology should you choose?

• A.ELT
• B.ETL
• C.ETLT
• D.EL