LATEST ASSOCIATE-DATA-PRACTITIONER EXAM PASS4SURE & ASSOCIATE-DATA-PRACTITIONER EXAM CONSULTANT

Latest Associate-Data-Practitioner Exam Pass4sure & Associate-Data-Practitioner Exam Consultant

Latest Associate-Data-Practitioner Exam Pass4sure & Associate-Data-Practitioner Exam Consultant

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Google Cloud Associate Data Practitioner Sample Questions (Q28-Q33):

NEW QUESTION # 28
You are responsible for managing Cloud Storage buckets for a research company. Your company has well-defined data tiering and retention rules. You need to optimize storage costs while achieving your data retention needs. What should you do?

  • A. Configure a lifecycle management policy on each bucket to downgrade the storage class and remove objects based on age.
  • B. Configure the buckets to use the Autoclass feature.
  • C. Configure the buckets to use the Archive storage class.
  • D. Configure the buckets to use the Standard storage class and enable Object Versioning.

Answer: A

Explanation:
Configuring a lifecycle management policy on each Cloud Storage bucket allows you to automatically transition objects to lower-cost storage classes (such as Nearline, Coldline, or Archive) based on their age or other criteria. Additionally, the policy can automate the removal of objects once they are no longer needed, ensuring compliance with retention rules and optimizing storage costs. This approach aligns well with well-defined data tiering and retention needs, providing cost efficiency and automation.


NEW QUESTION # 29
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 Admin role.
  • B. Request the Dataflow Worker role.
  • C. Request the Dataflow Viewer role.
  • D. Request the Dataflow Developer role.

Answer: D

Explanation:
The Dataflow Developer role provides the necessary permissions to manage Dataflow streaming pipelines, including the ability to restart pipelines. This role adheres to the principle of least privilege, as it grants only the permissions required to manage and operate Dataflow jobs without unnecessary administrative access. Other roles, such as Dataflow Admin, would grant broader permissions, which are not needed in this scenario.


NEW QUESTION # 30
You are a data analyst working with sensitive customer data in BigQuery. You need to ensure that only authorized personnel within your organization can query this data, while following the principle of least privilege. What should you do?

  • A. Encrypt the data by using customer-managed encryption keys (CMEK).
  • B. Update dataset privileges by using the SQL GRANT statement.
  • C. Export the data to Cloud Storage, and use signed URLs to authorize access.
  • D. Enable access control by using IAM roles.

Answer: D

Explanation:
Comprehensive and Detailed In-Depth Explanation:
BigQuery uses IAM for access control, adhering to least privilege by granting only necessary permissions.
* Option A: IAM roles (e.g., roles/bigquery.dataViewer for read-only) restrict query access to authorized users, aligning with Google's security best practices.
* Option B: BigQuery doesn't support SQL GRANT for dataset privileges; access is managed via IAM or authorized views.
* Option C: Exporting to Cloud Storage with signed URLs bypasses BigQuery's native controls and adds complexity.


NEW QUESTION # 31
You want to process and load a daily sales CSV file stored in Cloud Storage into BigQuery for downstream reporting. You need to quickly build a scalable data pipeline that transforms the data while providing insights into data quality issues. What should you do?

  • A. Load the CSV file as a table in BigQuery. Create a batch pipeline in Cloud Data Fusion by using a BigQuery source and sink.
  • B. Create a batch pipeline in Cloud Data Fusion by using a Cloud Storage source and a BigQuery sink.
  • C. Create a batch pipeline in Dataflow by using the Cloud Storage CSV file to BigQuery batch template.
  • D. Load the CSV file as a table in BigQuery, and use scheduled queries to run SQL transformation scripts.

Answer: B

Explanation:
Using Cloud Data Fusion to create a batch pipeline with a Cloud Storage source and a BigQuery sink is the best solution because:
Scalability: Cloud Data Fusion is a scalable, fully managed data integration service.
Data transformation: It provides a visual interface to design pipelines, enabling quick transformation of data.
Data quality insights: Cloud Data Fusion includes built-in tools for monitoring and addressing data quality issues during the pipeline creation and execution process.


NEW QUESTION # 32
Your organization has several datasets in BigQuery. The datasets need to be shared with your external partners so that they can run SQL queries without needing to copy the data to their own projects. You have organized each partner's data in its own BigQuery dataset. Each partner should be able to access only their dat a. You want to share the data while following Google-recommended practices. What should you do?

  • A. Export the BigQuery data to a Cloud Storage bucket. Grant the partners the storage.objectUser IAM role on the bucket.
  • B. Create a Dataflow job that reads from each BigQuery dataset and pushes the data into a dedicated Pub/Sub topic for each partner. Grant each partner the pubsub. subscriber IAM role.
  • C. Grant the partners the bigquery.user IAM role on the BigQuery project.
  • D. Use Analytics Hub to create a listing on a private data exchange for each partner dataset. Allow each partner to subscribe to their respective listings.

Answer: D

Explanation:
Using Analytics Hub to create a listing on a private data exchange for each partner dataset is the Google-recommended practice for securely sharing BigQuery data with external partners. Analytics Hub allows you to manage data sharing at scale, enabling partners to query datasets directly without needing to copy the data into their own projects. By creating separate listings for each partner dataset and allowing only the respective partner to subscribe, you ensure that partners can access only their specific data, adhering to the principle of least privilege. This approach is secure, efficient, and designed for scenarios involving external data sharing.


NEW QUESTION # 33
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