Try and practice the latest Google : ADP real questions & answers
Updated: Sep 14, 2026
No. of Questions: 66 Questions & Answers with Testing Engine
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Google ADP Exam Overview:
| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Associate Data Practitioner |
| Exam Number: | PCA-DP |
| Real Exam Qty: | 50 |
| Available Languages: | English |
| Exam Format: | Multiple Choice, Multiple Select |
| Related Certifications: | Google Cloud Data Analytics Google Cloud Professional Data Engineer Looker Data Analyst |
| Exam Price: | USD 100 |
| Certificate Validity Period: | 24 months |
| Passing Score: | 70 |
| Exam Duration: | 120 minutes |
| Sample Questions: | Google ADP Sample Questions |
| Exam Way: | Online proctored or in-person testing center |
| Pre Condition: | No formal prerequisites, but basic knowledge of data concepts and cloud computing is recommended |
| Official Syllabus URL: | https://cloud.google.com/certification/associate-data-practitioner |
Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data-Driven Decision Making | 10-20% | - Assess data quality and completeness - Translate business requirements into data solutions - Identify stakeholders and requirements - Define success metrics |
| Topic 2: Data Processing and Analytics | 20-30% | - Use BigQuery and SQL for analytics - Apply statistical methods for analysis - Build and maintain data pipelines - Query and analyze datasets - Aggregate and summarize data |
| Topic 3: Data Preparation and Exploration | 20-30% | - Identify data quality issues - Ingest and acquire data - Transform and prepare data for analysis - Perform exploratory data analysis (EDA) - Explore data through visualization and queries |
| Topic 4: Data Visualization and Insights | 20-30% | - Choose appropriate visualization types - Interpret and communicate findings - Build visualizations using Looker Studio - Create dashboards and reports - Present data insights to stakeholders |
Google Associate Data Practitioner Sample Questions:
You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?
- A. Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
- B. Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.
- C. Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
- D. Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
Correct Answer: A 🗳️
You have a BigQuery dataset containing sales dat
a. 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. 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.
- B. Use BigQuery long-term storage for the entire dataset. Set up a Cloud Run function to delete the data from BigQuery after 3 years.
- 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. Store all data in a single BigQuery table without partitioning or lifecycle policies.
Correct Answer: A 🗳️
You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?
- A. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.
- B. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
- C. Use Cloud Client Libraries to transfer the data over the internet.
- D. Use the gcloud storage command to transfer the data over the internet.
Correct Answer: B 🗳️
Your company uses Looker to generate and share reports with various stakeholders. You have a complex dashboard with several visualizations that needs to be delivered to specific stakeholders on a recurring basis, with customized filters applied for each recipient. You need an efficient and scalable solution to automate the delivery of this customized dashboard. You want to follow the Google- recommended approach. What should you do?
- A. Create a script using the Looker Python SDK, and configure user attribute filter values. Generate a new scheduled plan for each stakeholder.
- B. Create a separate LookML model for each stakeholder with predefined filters, and schedule the dashboards using the Looker Scheduler.
- C. Use the Looker Scheduler with a user attribute filter on the dashboard, and send the dashboard with personalized filters to each stakeholder based on their attributes.
- D. Embed the Looker dashboard in a custom web application, and use the application's scheduling features to send the report with personalized filters.
Correct Answer: C 🗳️
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 gcloud storage commands.
- B. Use Cloud Storage FUSE.
- C. Use a Transfer Appliance.
- D. Use Storage Transfer Service.
Correct Answer: D 🗳️
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