PASS GUARANTEED 2025 RELIABLE GOOGLE ASSOCIATE-DATA-PRACTITIONER CERTIFICATION SAMPLE QUESTIONS

Pass Guaranteed 2025 Reliable Google Associate-Data-Practitioner Certification Sample Questions

Pass Guaranteed 2025 Reliable Google Associate-Data-Practitioner Certification Sample Questions

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Google Associate-Data-Practitioner Exam Syllabus Topics:

TopicDetails
Topic 1
  • Data Preparation and Ingestion: This section of the exam measures the skills of Google Cloud Engineers and covers the preparation and processing of data. Candidates will differentiate between various data manipulation methodologies such as ETL, ELT, and ETLT. They will choose appropriate data transfer tools, assess data quality, and conduct data cleaning using tools like Cloud Data Fusion and BigQuery. A key skill measured is effectively assessing data quality before ingestion.
Topic 2
  • Data Management: This domain measures the skills of Google Database Administrators in configuring access control and governance. Candidates will establish principles of least privilege access using Identity and Access Management (IAM) and compare methods of access control for Cloud Storage. They will also configure lifecycle management rules to manage data retention effectively. A critical skill measured is ensuring proper access control to sensitive data within Google Cloud services
Topic 3
  • Data Analysis and Presentation: This domain assesses the competencies of Data Analysts in identifying data trends, patterns, and insights using BigQuery and Jupyter notebooks. Candidates will define and execute SQL queries to generate reports and analyze data for business questions.| Data Pipeline Orchestration: This section targets Data Analysts and focuses on designing and implementing simple data pipelines. Candidates will select appropriate data transformation tools based on business needs and evaluate use cases for ELT versus ETL.

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Google Cloud Associate Data Practitioner Sample Questions (Q51-Q56):

NEW QUESTION # 51
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 the buckets to use the Standard storage class and enable Object Versioning.
  • B. Configure the buckets to use the Archive storage class.
  • C. Configure a lifecycle management policy on each bucket to downgrade the storage class and remove objects based on age.
  • D. Configure the buckets to use the Autoclass feature.

Answer: C

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 # 52
You are a Looker analyst. You need to add a new field to your Looker report that generates SQL that will run against your company's database. You do not have the Develop permission. What should you do?

  • A. Create a calculated field using the Add a field option in Looker Studio, and add it to your report.
  • B. Create a custom field from the field picker in Looker, and add it to your report.
  • C. Create a new field in the LookML layer, refresh your report, and select your new field from the field picker.
  • D. Create a table calculation from the field picker in Looker, and add it to your report.

Answer: B

Explanation:
Creating a custom field from the field picker in Looker allows you to add new fields to your report without requiring the Develop permission. Custom fields are created directly in the Looker UI, enabling you to define calculations or transformations that generate SQL for the database query. This approach is user-friendly and does not require access to the LookML layer, making it the appropriate choice for your situation.


NEW QUESTION # 53
Your company has developed a website that allows users to upload and share video files. These files are most frequently accessed and shared when they are initially uploaded. Over time, the files are accessed and shared less frequently, although some old video files may remain very popular.
You need to design a storage system that is simple and cost-effective. What should you do?

  • A. Create a single-region bucket with Autoclass enabled.
  • B. Create a single-region bucket with custom Object Lifecycle Management policies based on upload date.
  • C. Create a single-region bucket with Archive as the default storage class.
  • D. Create a single-region bucket. Configure a Cloud Scheduler job that runs every 24 hours and changes the storage class based on upload date.

Answer: B

Explanation:
Creating a single-region bucket with custom Object Lifecycle Management policies based on upload date is the most appropriate solution. This approach allows you to automatically transition objects to less expensive storage classes as their access frequency decreases over time. For example, frequently accessed files can remain in the Standard storage class initially, then transition to Nearline, Coldline, or Archive storage as their popularity wanes. This strategy ensures a cost-effective and efficient storage system while maintaining simplicity by automating the lifecycle management of video files.


NEW QUESTION # 54
Your team is building several data pipelines that contain a collection of complex tasks and dependencies that you want to execute on a schedule, in a specific order. The tasks and dependencies consist of files in Cloud Storage, Apache Spark jobs, and data in BigQuery. You need to design a system that can schedule and automate these data processing tasks using a fully managed approach. What should you do?

  • A. Use Cloud Tasks to schedule and run the jobs asynchronously.
  • B. Create directed acyclic graphs (DAGs) in Apache Airflow deployed on Google Kubernetes Engine. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
  • C. Use Cloud Scheduler to schedule the jobs to run.
  • D. Create directed acyclic graphs (DAGs) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.

Answer: D

Explanation:
Using Cloud Composer to create Directed Acyclic Graphs (DAGs) is the best solution because it is a fully managed, scalable workflow orchestration service based on Apache Airflow. Cloud Composer allows you to define complex task dependencies and schedules while integrating seamlessly with Google Cloud services such as Cloud Storage, BigQuery, and Dataproc for Apache Spark jobs. This approach minimizes operational overhead, supports scheduling and automation, and provides an efficient and fully managed way to orchestrate your data pipelines.


NEW QUESTION # 55
Your organization has several datasets in their data warehouse in BigQuery. Several analyst teams in different departments use the datasets to run queries. Your organization is concerned about the variability of their monthly BigQuery costs. You need to identify a solution that creates a fixed budget for costs associated with the queries run by each department. What should you do?

  • A. Assign each analyst to a separate project associated with their department. Create a single reservation by using BigQuery editions. Assign all projects to the reservation.
  • B. Assign each analyst to a separate project associated with their department. Create a single reservation for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
  • C. Create a custom quota for each analyst in BigQuery.
  • D. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.

Answer: B

Explanation:
Assigning each analyst to a separate project associated with their department and creating a single reservation for each department using BigQuery editions allows for precise cost management. By assigning each project to its department's reservation, you can allocate fixed compute resources and budgets for each department, ensuring that their query costs are predictable and controlled. This approach aligns with your organization's goal of creating a fixed budget for query costs while maintaining departmental separation and accountability.


NEW QUESTION # 56
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