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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Workflow orchestration concepts (e.g., Cloud Composer) 2. Dataflow pipelines
Data Management	25%	- Storage and data organization 1. Cloud Storage lifecycle policies 2. BigQuery datasets and tables management - Data governance and security 1. IAM and access control 2. Data lifecycle management
Data Analysis and Presentation	27%	- Querying and analyzing data 1. BigQuery SQL usage 2. Data aggregation and transformation - Data visualization 1. Looker / Looker Studio reporting
Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Cloud Storage ingestion patterns 2. Streaming ingestion with Pub/Sub concepts

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Google Associate Data Practitioner Sample Questions (Q20-Q25):

NEW QUESTION # 20
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. Copy the storm event dataset into your BigQuery project. Use BigQuery Studio to query and visualize the data in Looker Studio.
B. 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.
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. 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.

Answer: A

NEW QUESTION # 21
You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost- effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?

A. Use Dataproc to run MapReduce jobs for distributed data processing.
B. Use Cloud Data Fusion to visually design and manage the pipelines.
C. Use Cloud Composer to orchestrate and run data workflows.
D. Use Dataform to build, orchestrate, and monitor the pipelines.

Answer: D

NEW QUESTION # 22
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 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.
C. Create a table with the aggregated performance data. Use table-level permissions to grant access to the payroll specialist.
D. 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.

Answer: A

NEW QUESTION # 23
Your company wants to implement a data transformation (ETL) pipeline for their BigQuery data warehouse.
You need to identify a managed transformation solution that allows users to develop with SQL and JavaScript, has version control, allows for modular code, and has data quality checks. What should you do?

A. Use Dataproc to create an Apache Spark cluster and implement the transformations by using PySpark SQL.
B. Use Dataform to define the transformations in SQLX.
C. Create BigQuery scheduled queries to define the transformations in SQL.
D. Create a Cloud Composer environment, and orchestrate the transformations by using the BigQueryinsertJob operator.

Answer: B

NEW QUESTION # 24
Your company currently uses an on-premises network file system (NFS) and is migrating data to Google Cloud. You want to be able to control how much bandwidth is used by the data migration while capturing detailed reporting on the migration status. What should you do?

A. Use Cloud Storage FUSE.
B. Use Storage Transfer Service.
C. Use gcloud storage commands.
D. Use a Transfer Appliance.

Answer: B

NEW QUESTION # 25
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