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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Preparation and Ingestion | 30% | - Data extraction and transfer tools
|
| Data Analysis and Presentation | 27% | - Data visualization and reporting
|
| Data Management and Governance | 25% | - Data security and access control
|
| Data Pipeline Orchestration | 18% | - Pipeline automation and scheduling
|
Google Associate Data Practitioner Sample Questions:
Question 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.
Question 2
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 Viewer role.
B. Request the Dataflow Admin role.
C. Request the Dataflow Worker role.
D. Request the Dataflow Developer role.
Question 3
Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?
A. Use Dataflow pipelines.
B. Use Dataform workflows.
C. Use Cloud Data Fusion pipelines.
D. Use Cloud Composer operators.
Question 4
You have a Dataproc cluster that performs batch processing on data stored in Cloud Storage. You need to schedule a daily Spark job to generate a report that will be emailed to stakeholders. You need a fully-managed solution that is easy to implement and minimizes complexity. What should you do?
A. Use Cloud Run functions to trigger the Spark job and email the report.
B. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.
C. Use Cloud Composer to orchestrate the Spark job and email the report.
D. Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.
Question 5
Following a recent company acquisition, you inherited an on- premises data infrastructure that needs to move to Google Cloud. The acquired system has 250 Apache Airflow directed acyclic graphs (DAGs) orchestrating data pipelines. You need to migrate the pipelines to a Google Cloud managed service with minimal effort. What should you do?
A. Create a Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
B. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.
C. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.
D. Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
Solutions:
| Question 1 Answer: B | Question 2 Answer: D | Question 3 Answer: B | Question 4 Answer: D | Question 5 Answer: C |

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