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Google Associate-Data-Practitioner Exam Syllabus Topics:

Topic	Details
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 (Q49-Q54):

NEW QUESTION # 49
You have a BigQuery dataset containing sales data. This data is actively queried for the first 6 months. After that, the data is not queried but needs to be retained for 3 years for compliance reasons. You need to implement a data management strategy that meets access and compliance requirements, while keeping cost and administrative overhead to a minimum. What should you do?

A. Use BigQuery long-term storage for the entire dataset. Set up a Cloud Run function to delete the data from BigQuery after 3 years.
B. Store all data in a single BigQuery table without partitioning or lifecycle policies.
C. Set up a scheduled query to export the data to Cloud Storage after 6 months. Write a stored procedure to delete the data from BigQuery after 3 years.
D. Partition a BigQuery table by month. After 6 months, export the data to Coldline storage. Implement a lifecycle policy to delete the data from Cloud Storage after 3 years.

Answer: D

Explanation:
Partitioning the BigQuery table by month allows efficient querying of recent data for the first 6 months, reducing query costs. After 6 months, exporting the data toColdline storageminimizes storage costs for data that is rarely accessed but needs to be retained for compliance. Implementing a lifecycle policy in Cloud Storage automates the deletion of the data after 3 years, ensuring compliance while reducing administrative overhead. This approach balances cost efficiency and compliance requirements effectively.

NEW QUESTION # 50
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 Dataflow pipelines.
B. Use Cloud Composer operators.
C. Use Cloud Data Fusion pipelines.
D. Use Dataform workflows.

Answer: D

Explanation:
Dataform workflows are the ideal solution for migrating batch transformation pipelines to Google Cloud when you want to perform programmatic transformations using only SQL. Dataform allows you to define SQL-based workflows for data transformations and supports Git integration for version control, enabling collaboration and version tracking of your pipelines. This approach is purpose-built for SQL-driven data pipeline management and aligns perfectly with your requirements.

NEW QUESTION # 51
Your company is setting up an enterprise business intelligence platform. You need to limit data access between many different teams while following the Google-recommended approach. What should you do first?

A. Create a separate Looker Studio report for each team, and share each report with the individuals within each team.
B. Create a Looker (Google Cloud core) instance, and create a separate dashboard for each team.
C. Create one Looker Studio report with multiple pages, and add each team's data as a separate data source to the report.
D. Create a Looker (Google Cloud core) instance, and configure different Looker groups for each team.

Answer: D

Explanation:
Comprehensive and Detailed In-Depth Explanation:
For an enterprise BI platform with data access control across teams, Google recommends Looker (Google Cloud core) over Looker Studio for its robust access management. The "first" step focuses on setting up the foundation.
* Option A: Looker Studio reports are lightweight but lack granular access control beyond sharing.
Creating separate reports per team is inefficient and unscalable.
* Option B: One Looker Studio report with multiple pages and data sources doesn't enforce team-level access control natively-users could access all pages/data.
* Option C: Creating a Looker instance with separate dashboards per team is a step forward but skips the foundational access control setup (groups), reducing scalability.

NEW QUESTION # 52
Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?

A. Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.
B. Create a view that filters out rows that are older than one year.
C. Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.
D. Require users to specify a partition filter using the alter table statement in SQL.

Answer: C

Explanation:
Setting the table partition expiration period to one year using the ALTER TABLE statement is the most efficient and cost-effective approach. This automatically deletes data in partitions older than one year, reducing storage costs without requiring manual intervention or additional queries. It minimizes administrative overhead and ensures compliance with your data retention policy while optimizing storage usage in BigQuery.

NEW QUESTION # 53
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 for each department by using BigQuery editions. Create assignments for each project in the appropriate reservation.
B. Create a custom quota for each analyst in BigQuery.
C. 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.
D. Create a single reservation by using BigQuery editions. Assign all analysts to the reservation.

Answer: A

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 # 54
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