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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Management and Governance | 25% | - Compliance and governance
|
| Data Preparation and Ingestion | 30% | - Storage solutions selection
|
| Data Pipeline Orchestration | 18% | - Pipeline automation and scheduling
|
| Data Analysis and Presentation | 27% | - Data exploration and analysis
|
Google Associate Data Practitioner Sample Questions:
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 Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
- B. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
- C. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
- D. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
Correct Answer: A 🗳️
Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?
- A. Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.
- B. Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
- C. Create a single Explore with all sales metrics. Build the dashboard using this Explore.
- D. Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
Correct Answer: C 🗳️
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 Composer to orchestrate the Spark job and email the report.
- B. Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.
- C. Use Cloud Run functions to trigger the Spark job and email the report.
- D. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.
Correct Answer: B 🗳️
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 separate LookML model for each stakeholder with predefined filters, and schedule the dashboards using the Looker Scheduler.
- B. Embed the Looker dashboard in a custom web application, and use the application's scheduling features to send the report with personalized filters.
- C. 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.
- D. Create a script using the Looker Python SDK, and configure user attribute filter values. Generate a new scheduled plan for each stakeholder.
Correct Answer: C 🗳️
Your organization has decided to migrate their existing enterprise data warehouse to BigQuery. The existing data pipeline tools already support connectors to BigQuery. You need to identify a data migration approach that optimizes migration speed. What should you do?
- A. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.
- B. Use the BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
- C. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
- D. Create a temporary file system to facilitate data transfer from the existing environment to Cloud Storage. Use Storage Transfer Service to migrate the data into BigQuery.
Correct Answer: C 🗳️
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