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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. You created a curated dataset of market trends in BigQuery that you want to share with multiple external partners. You want to control the rows and columns that each partner has access to. You want to follow Google-recommended practices. What should you do?

A) Create a separate project for each partner and copy the dataset into each project. Publish each dataset in Analytics Hub. Grant dataset-level access to each partner by using subscriptions.
B) Grant each partner read access to the BigQuery dataset by using 1AM roles.
C) Create a separate Cloud Storage bucket for each partner. Export the dataset to each bucket and assign each partner to their respective bucket. Grant bucket-level access by using 1AM roles.
D) Publish the dataset in Analytics Hub. Grant dataset-level access to each partner by using subscriptions.

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

3. Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A) Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
B) Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.
C) Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.
D) Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.

4. You have a Dataflow pipeline that processes website traffic logs stored in Cloud Storage and writes the processed data to BigQuery. You noticed that the pipeline is failing intermittently. You need to troubleshoot the issue. What should you do?

A) Use Cloud Logging to create a chart displaying the pipeline's error logs. Use Metrics Explorer to validate the findings from the chart.
B) Use Cloud Logging to view error messages in the pipeline's logs. Use Cloud Monitoring to analyze the pipeline's metrics, such as CPU utilization and memory usage.
C) Use the Dataflow job monitoring interface to check the pipeline's status every hour. Use Cloud Profiler to analyze the pipeline's metrics, such as CPU utilization and memory usage.
D) Use Cloud Logging to identify error groups in the pipeline's logs. Use Cloud Monitoring to create a dashboard that tracks the number of errors in each group.

5. You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?

A) Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
B) Use the gcloud storage command to transfer the data over the internet.
C) Use Cloud Client Libraries to transfer the data over the internet.
D) Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.

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