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Google Associate Data Practitioner Sample Questions:

1. 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 Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
C) Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
D) Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.

2. You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?

A) Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
B) Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.
C) Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
D) Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.

3. You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need toclean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

A) Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.
B) Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.
C) Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.
D) Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.

4. Your team is building several data pipelines that contain a collection of complex tasks and dependencies that you want to execute on a schedule, in a specific order. The tasks and dependencies consist of files in Cloud Storage, Apache Spark jobs, and data in BigQuery. You need to design a system that can schedule and automate these data processing tasks using a fully managed approach. What should you do?

A) Use Cloud Scheduler to schedule the jobs to run.
B) Create directed acyclic graphs (DAGS) in Apache Airflow deployed on Google Kubernetes Engine. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
C) Create directed acyclic graphs (DAGS) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
D) Use Cloud Tasks to schedule and run the jobs asynchronously.

5. You recently inherited a task for managing Dataflow streaming pipelines in your organization and noticed that proper access had not been provisioned to you. You need to request a Google-provided IAM role so you can restart the pipelines. You need to follow the principle of least privilege. What should you do?

A) Request the Dataflow Worker role.
B) Request the Dataflow Developer role.
C) Request the Dataflow Viewer role.
D) Request the Dataflow Admin role.

Solutions: