Google BigQuery
The Google BigQuery exam assesses individuals' proficiency in working with Google's cloud-based data warehouse solution, BigQuery. This exam evaluates candidates' ability to perform data analysis, query optimization, and data manipulation tasks using BigQuery's SQL-like querying language and advanced analytics features. Successful candidates demonstrate skills in data modeling, schema design, query performance tuning, and leveraging BigQuery's scalability and integration capabilities to derive insights and make data-driven decisions.
Who should take the exam?
- Data Analysts: Data analysts, business analysts, and data scientists interested in leveraging BigQuery for data exploration, ad-hoc analysis, and deriving insights from large datasets.
- Data Engineers: Data engineers, ETL developers, and database administrators responsible for designing and optimizing data pipelines, data models, and schema structures in BigQuery.
- Business Intelligence Professionals: Business intelligence (BI) developers, dashboard designers, and reporting analysts looking to build interactive dashboards, reports, and visualizations using BigQuery data.
- Cloud Architects: Cloud architects, solution architects, and technical leads involved in designing and implementing data analytics solutions using Google Cloud Platform (GCP) services, including BigQuery.
- Developers: Software developers, application developers, and software engineers interested in integrating BigQuery into custom applications, workflows, and analytics solutions.
Course Outline
The Google BigQuery exam covers the following topics :-
- Module 1: Introduction to Google BigQuery
- Module 2: Understanding Data Modeling and Schema Design
- Module 3: Understanding Querying and Data Manipulation
- Module 4: Understanding Query Optimization Techniques
- Module 5: Understanding Advanced Analytics and Machine Learning
- Module 6: Understanding Data Visualization and Reporting
- Module 7: Understanding Data Security and Access Control
- Module 8: Understanding Data Integration and ETL
- Module 9: Understanding Cost Management and Optimization
- Module 10: Understanding Real-world Use Cases and Best Practices
Google BigQuery FAQs
What is the format of the exam?
The exam includes 60 multiple‑choice questions and 5 scenario‑based case studies. You have 90 minutes to complete it.
Who should take the exam?
Professionals who design, manage, or analyse data solutions on Google BigQuery, including analysts, engineers, and architects.
Is prior BigQuery experience required?
Basic SQL and cloud‑data knowledge help, but the exam covers both foundational and advanced BigQuery topics.
How can I prepare?
Practice in a live BigQuery environment, load sample datasets, write advanced SQL queries, and explore each domain in the Google Cloud documentation.
What score is required to pass?
A minimum score of 70% overall is required to earn certification.
Can I retake the exam if I fail?
Yes. You may retake it after a 14‑day waiting period.
How long is certification valid?
Certification remains valid for three years. Renewal requires passing a brief refresher assessment.
What tools do I need for the exam?
A Google Cloud account with BigQuery enabled, a web browser, and a calculator for simple cost and slot calculations.
Are practical tasks included?
Yes. Scenario‑based tasks test your ability to load data, optimise queries, configure security, and automate workflows.
How will this certification benefit me?
It validates your BigQuery expertise, enhancing credibility in roles involving data engineering, analytics, and cloud architecture.