Exam Name: Associate Data Practitioner
Certification Provider: Google
Corresponding Certification: Google Cloud Certified
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Instant Download Google : ADP Questions & Answers as PDF & Test Engine
Updated: Sep 16, 2026
No. of Questions: 66 Questions & Answers with Testing Engine
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Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Visualization and Insights | 20-30% | - Create dashboards and reports - Present data insights to stakeholders - Interpret and communicate findings - Choose appropriate visualization types - Build visualizations using Looker Studio |
| Topic 2: Data Processing and Analytics | 20-30% | - Apply statistical methods for analysis - Use BigQuery and SQL for analytics - Query and analyze datasets - Aggregate and summarize data - Build and maintain data pipelines |
| Topic 3: Data Preparation and Exploration | 20-30% | - Identify data quality issues - Transform and prepare data for analysis - Perform exploratory data analysis (EDA) - Ingest and acquire data - Explore data through visualization and queries |
| Topic 4: Data-Driven Decision Making | 10-20% | - Define success metrics - Identify stakeholders and requirements - Translate business requirements into data solutions - Assess data quality and completeness |
Google Associate Data Practitioner Sample Questions:
You are working with a small dataset in Cloud Storage that needs to be transformed and loaded into BigQuery for analysis. The transformation involves simple filtering and aggregation operations. You want to use the most efficient and cost-effective data manipulation approach. What should you do?
- A. Use Dataflow to perform the ETL process that reads the data from Cloud Storage, transforms it using Apache Beam, and writes the results to BigQuery.
- B. Use BigQuery's SQL capabilities to load the data from Cloud Storage, transform it, and store the results in a new BigQuery table.
- C. Create a Cloud Data Fusion instance and visually design an ETL pipeline that reads data from Cloud Storage, transforms it using built-in transformations, and loads the results into BigQuery.
- D. Use Dataproc to create an Apache Hadoop cluster, perform the ETL process using Apache Spark, and load the results into BigQuery.
Correct Answer: B 🗳️
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 Dataform workflows.
- C. Use Cloud Composer operators.
- D. Use Cloud Data Fusion pipelines.
Correct Answer: B 🗳️
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 Cloud Composer to orchestrate and run data workflows.
- B. Use Dataform to build, orchestrate, and monitor the pipelines.
- C. Use Cloud Data Fusion to visually design and manage the pipelines.
- D. Use Dataproc to run MapReduce jobs for distributed data processing.
Correct Answer: B 🗳️
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. Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.
- B. Use Colab Enterprise to develop a custom model for purchase prediction.
- C. Use Vertex Al Workbench to develop a custom model for purchase prediction.
- D. Use BigQuery ML to create a logistic regression model for purchase prediction.
Correct Answer: D 🗳️
You have a Dataproc cluster that performs batch processing on data stored in Cloud Storage. You need to schedule a daily Spark job to generate a report that will be emailed to stakeholders. You need a fully-managed solution that is easy to implement and minimizes complexity. What should you do?
- A. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.
- B. Use Cloud Composer to orchestrate the Spark job and email the report.
- C. Use Cloud Run functions to trigger the Spark job and email the report.
- D. Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.
Correct Answer: D 🗳️
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