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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Preparation and Ingestion | 30% | - Storage solutions selection
|
| Data Pipeline Orchestration | 18% | - Pipeline automation and scheduling
|
| Data Analysis and Presentation | 27% | - Data visualization and reporting
|
| Data Management and Governance | 25% | - Data quality and maintenance
|
Google Associate Data Practitioner Sample Questions:
You work for a home insurance company. You are frequently asked to create and save risk reports with charts for specific areas using a publicly available storm event dataset. You want to be able to quickly create and re- run risk reports when new data becomes available. What should you do?
- A. Reference and query the storm event dataset using SQL in BigQuery Studio. Export the results to Google Sheets, and use cell data in the worksheets to create charts.
- B. Copy the storm event dataset into your BigQuery project. Use BigQuery Studio to query and visualize the data in Looker Studio.
- C. Reference and query the storm event dataset using SQL in a Colab Enterprise notebook. Display the table results and document with Markdown, and use Matplotlib to create charts.
- D. Export the storm event dataset as a CSV file. Import the file to Google Sheets, and use cell data in the worksheets to create charts.
Correct Answer: B 🗳️
You are working on a project that requires analyzing daily social media dat a. You have 100 GB of JSON formatted data stored in Cloud Storage that keeps growing.
You need to transform and load this data into BigQuery for analysis. You want to follow the Google-recommended approach. What should you do?
- A. Manually download the data from Cloud Storage. Use a Python script to transform and upload the data into BigQuery.
- B. Use Cloud Run functions to transform and load the data into BigQuery.
- C. Use Cloud Data Fusion to transfer the data into BigQuery raw tables, and use SQL to transform it.
- D. Use Dataflow to transform the data and write the transformed data to BigQuery.
Correct Answer: D 🗳️
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. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
- C. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
- D. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.
Correct Answer: B 🗳️
You used BigQuery ML to build a customer purchase propensity model six months ago. You want to compare the current serving data with the historical serving data to determine whether you need to retrain the model.
What should you do?
- A. Compare the two different models.
- B. Evaluate data drift.
- C. Evaluate the data skewness.
- D. Compare the confusion matrix.
Correct Answer: B 🗳️
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 Cloud Composer operators.
- B. Use Cloud Data Fusion pipelines.
- C. Use Dataform workflows.
- D. Use Dataflow pipelines.
Correct Answer: C 🗳️
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