Google ADP : Associate Data Practitioner

  • Exam Code: ADP
  • Exam Name: Associate Data Practitioner
  • Updated: Sep 18, 2026
  • Q & A: 66 Questions and Answers

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About Google ADP Exam

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Google ADP Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Analysis and Presentation27%- Business intelligence and decision support
  • 1. Answer business questions with data
  • 2. Communicate findings effectively
- Data exploration and analysis
  • 1. BigQuery SQL queries
  • 2. Jupyter notebooks for analysis
  • 3. Identify trends, patterns, insights
- Data visualization and reporting
  • 1. Looker dashboards and reports
  • 2. Visualization best practices
Topic 2: Data Management and Governance25%- Compliance and governance
  • 1. Data privacy and regulatory requirements
  • 2. Data stewardship and cataloging
- Data security and access control
  • 1. IAM roles and permissions
  • 2. Data encryption and protection
- Data quality and maintenance
  • 1. Data validation and cleaning
  • 2. Data lifecycle management
Topic 3: Data Preparation and Ingestion30%- Data extraction and transfer tools
  • 1. Cloud Data Fusion, Storage Transfer Service
  • 2. Dataflow, BigQuery Data Transfer Service, Database Migration Service
- Storage solutions selection
  • 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner
  • 2. Storage location types: regional, dual-regional, multi-regional, zonal
- Data loading methods
  • 1. gcloud, BQ CLI, client libraries
  • 2. Batch and streaming ingestion
- Data formats and classification
  • 1. Structured, semi-structured, unstructured data
  • 2. Formats: CSV, JSON, Parquet, Avro, database tables
Topic 4: Data Pipeline Orchestration18%- Transformation tools selection
  • 1. Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform
- Pipeline automation and scheduling
  • 1. Error handling and monitoring
  • 2. Schedule and monitor data jobs
- Data transformation concepts
  • 1. ETL vs ELT processes
  • 2. Data transformation requirements

Google Associate Data Practitioner Sample Questions:

Question #1

You are a data analyst working with sensitive customer data in BigQuery. You need to ensure that only authorized personnel within your organization can query this data, while following the principle of least privilege. What should you do?

  • A. Encrypt the data by using customer-managed encryption keys (CMEK).
  • B. Update dataset privileges by using the SQL GRANT statement.
  • C. Enable access control by using IAM roles.
  • D. Export the data to Cloud Storage, and use signed URLs to authorize access.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Question #2

Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

  • A. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.
  • B. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
  • C. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.
  • D. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables. Use the row_number() window function to query the new materialized view.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #3

Your organization uses scheduled queries to perform transformations on data stored in BigQuery. You discover that one of your scheduled queries has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

  • A. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.
  • B. Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.
  • C. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.
  • D. Set up a log sink using the gcloud CLI to export BigQuery audit logs to BigQuery. Query those logs to identify the error associated with the failed job I
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #4

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 Dataproc workflow templates to define and schedule the Spark job, and to email the report.
  • B. Use Cloud Run functions to trigger the Spark job and email the report.
  • C. Use Cloud Composer to orchestrate the Spark job and email the report.
  • D. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #5

Your company stores historical data in Cloud Storage. You need to ensure that all data is saved in a bucket for at least three years. What should you do?

  • A. Change the bucket storage class to Archive.
  • B. Enable Object Versioning.
  • C. Set a bucket retention policy.
  • D. Set temporary object holds.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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