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Last Updated: Oct 14, 2026

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Google ADP Exam Syllabus Topics:

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

Google Associate Data Practitioner Sample Questions:

Question #1

Your organization has several datasets in BigQuery. The datasets need to be shared with your external partners so that they can run SQL queries without needing to copy the data to their own projects. You have organized each partner's data in its own BigQuery dataset. Each partner should be able to access only their dat a. You want to share the data while following Google-recommended practices. What should you do?

  • A. Use Analytics Hub to create a listing on a private data exchange for each partner dataset. Allow each partner to subscribe to their respective listings.
  • B. Export the BigQuery data to a Cloud Storage bucket. Grant the partners the storage.objectUser IAM role on the bucket.
  • C. Create a Dataflow job that reads from each BigQuery dataset and pushes the data into a dedicated Pub /Sub topic for each partner. Grant each partner the pubsub. subscriber IAM role.
  • D. Grant the partners the bigquery.user IAM role on the BigQuery project.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #2

You have a Dataflow pipeline that processes website traffic logs stored in Cloud Storage and writes the processed data to BigQuery. You noticed that the pipeline is failing intermittently. You need to troubleshoot the issue. What should you do?

  • A. Use Cloud Logging to identify error groups in the pipeline's logs. Use Cloud Monitoring to create a dashboard that tracks the number of errors in each group.
  • B. Use the Dataflow job monitoring interface to check the pipeline's status every hour. Use Cloud Profiler to analyze the pipeline's metrics, such as CPU utilization and memory usage.
  • C. Use Cloud Logging to view error messages in the pipeline's logs. Use Cloud Monitoring to analyze the pipeline's metrics, such as CPU utilization and memory usage.
  • D. Use Cloud Logging to create a chart displaying the pipeline's error logs. Use Metrics Explorer to validate the findings from the chart.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Question #3

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. 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.
  • 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. 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.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #4

Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

  • A. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
  • B. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
  • C. Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
  • D. Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #5

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. Use the gcloud storage command to transfer the data over the internet.
  • B. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.
  • C. Use Cloud Client Libraries to transfer the data over the internet.
  • D. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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