ADP Practice Materials are highly similar to the real exam. ADP Study Guide covers all knowledge points for the customers. ADP Preparation Questions have been adapted and compiled carefully to ensure they are suitable for all people.

Google ADP exam : Associate Data Practitioner

ADP Exam Questions
  • Exam Code: ADP
  • Exam Name: Associate Data Practitioner
  • Updated: Jul 01, 2026
  • Q & A: 66 Questions and Answers
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Google Associate Data Practitioner Sample Questions:

1. 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 Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.
C) 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.
D) Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.


2. Your organization is building a new application on Google Cloud. Several data files will need to be stored in Cloud Storage. Your organization has approved only two specific cloud regions where these data files can reside. You need to determine a Cloud Storage bucket strategy that includes automated high availability.
What should you do?

A) Create a single-region bucket in each of the two regions, and use Storage Transfer Service to replicate the data across the buckets in both regions.
B) Create a single-region bucket in each of the two regions, and use the gcloud storage command to replicate the data across the buckets in both regions.
C) Create a multi-region bucket, and upload the files to this bucket.
D) Create a dual-region bucket, and upload the files to this bucket.


3. You are storing data in Cloud Storage for a machine learning project. The data is frequently accessed during the model training phase, minimally accessed after 30 days, and unlikely to be accessed after 90 days. You need to choose the appropriate storage class for the different stages of the project to minimize cost. What should you do?

A) Store the data in Standard storage during the model training phase. Transition the data to Durable Reduced Availability (DRA) storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
B) Store the data in Standard storage during the model training phase. Transition the data to Nearline storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
C) Store the data in Nearline storage during the model training phase. Transition the data to Coldline storage 30 days after model deployment, and to Archive storage 90 days after model deployment.
D) Store the data in Nearline storage during the model training phase. Transition the data to Archive storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.


4. You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

A) Use BigQuery ML to create a logistic regression model for purchase prediction.
B) Use Vertex Al Workbench to develop a custom model for purchase prediction.
C) Use Colab Enterprise to develop a custom model for purchase prediction.
D) Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.


5. 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 Dataform to build, orchestrate, and monitor the pipelines.
D) Use Cloud Composer to orchestrate and run data workflows.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: D
Question # 3
Answer: B
Question # 4
Answer: A
Question # 5
Answer: C

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