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Google Associate Data Practitioner Sample Questions:

1. 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 Dataform workflows.
B) Use Cloud Data Fusion pipelines.
C) Use Cloud Composer operators.
D) Use Dataflow pipelines.

2. Your organization plans to move their on-premises environment to Google Cloud. Your organization's network bandwidth is less than 1 Gbps. You need to move over 500 ## of data to Cloud Storage securely, and only have a few days to move the dat a. What should you do?

A) Connect to Google Cloud using VPN. Use Storage Transfer Service to move the data to Cloud Storage.
B) Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.
C) Connect to Google Cloud using Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.
D) Request multiple Transfer Appliances, copy the data to the appliances, and ship the appliances back to Google Cloud to upload the data to Cloud Storage.

3. Your organization has highly sensitive data that gets updated once a day and is stored across multiple datasets in BigQuery. You need to provide a new data analyst access to query specific data in BigQuery while preventing access to sensitive dat a. What should you do?

A) Grant the data analyst the BigQuery Job User IAM role in the Google Cloud project.
B) Grant the data analyst the BigQuery Data Viewer IAM role in the Google Cloud project.
C) Create a new Google Cloud project, and copy the limited data into a BigQuery table. Grant the data analyst the BigQuery Data Owner IAM role in the new Google Cloud project.
D) Create a materialized view with the limited data in a new dataset. Grant the data analyst BigQuery Data Viewer IAM role in the dataset and the BigQuery Job User IAM role in the Google Cloud project.

4. Your organization has a BigQuery dataset that contains sensitive employee information such as salaries and performance reviews. The payroll specialist in the HR department needs to have continuous access to aggregated performance data, but they do not need continuous access to other sensitive dat a. You need to grant the payroll specialist access to the performance data without granting them access to the entire dataset using the simplest and most secure approach. What should you do?

A) Use authorized views to share query results with the payroll specialist.
B) Create row-level and column-level permissions and policies on the table that contains performance data in the dataset. Provide the payroll specialist with the appropriate permission set.
C) Create a SQL query with the aggregated performance data. Export the results to an Avro file in a Cloud Storage bucket. Share the bucket with the payroll specialist.
D) Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.

5. Your company stores historical data in Cloud Storage. You need to ensure that all data is saved in a bucket for at least three years. What should you do?

A) Enable Object Versioning.
B) Change the bucket storage class to Archive.
C) Set temporary object holds.
D) Set a bucket retention policy.

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