Associate Data Practitioner Exam
Standard exam with 50 to 60 multiple-choice and multiple-select questions.
- Type
- Written
- Delivery
- Both
- Duration
- 120 min
Exam sections
Section 1: Data Preparation and Ingestion
Covers data preparation and ingestion processes, including selecting methodologies like ETL/ELT, choosing transfer tools, assessing data quality, and cleaning data. Focuses on extracting and loading data into appropriate Google Cloud storage systems using various formats and tools.
Preparation tips
Differentiate between ETL and ELT methodologies and understand the use cases for Storage Transfer Service vs. Transfer Appliance.
Section 2: Data Analysis and Presentation
Focuses on identifying data trends and insights using BigQuery SQL and Jupyter notebooks (Colab Enterprise). Includes visualization and dashboarding in Looker and Looker Studio, as well as defining, training, and evaluating ML models using BigQuery ML and AutoML.
Preparation tips
Focus on SQL for BigQuery, LookML parameters, and the lifecycle of an ML project from data collection to inference.
Section 3: Data Pipeline Orchestration
Addresses the design and implementation of data pipelines using tools such as Dataproc, Dataflow, and Cloud Data Fusion. Includes monitoring via Cloud Logging/Monitoring, orchestration with Cloud Composer and scheduled queries, and event-driven ingestion using Pub/Sub and Eventarc.
Preparation tips
Study orchestration solutions like Cloud Composer and scheduled queries, and understand event-driven pipeline triggers using Eventarc.
Section 4: Data Management
Covers access control and governance via IAM, lifecycle management for Cloud Storage and BigQuery, and disaster recovery strategies. Also focuses on security measures such as encryption keys (CMEK, CSEK, GMEK) and compliance with data privacy regulations.
Preparation tips
Review least privileged access principles and practice configuring lifecycle management rules to automate data deletion and archiving.