Exam facts
- Cost: Free (self-paced course)
- Duration: ~5 hours
- Format: Online guided tutorial
- Platform: learn.getdbt.com
- No formal exam required - completion of course is the certification pathway
- Prerequisite: Familiarity with SQL and basic data concepts
About
The dbt Fundamentals course is an entry-level, free guided tutorial that introduces you to dbt (data build tool) as a SQL-first transformation workflow. The course begins with dbt Cloud setup and ends with deploying your first project. You'll learn best practices for writing models, implementing tests, using the 'ref' function, and organizing dbt projects.
This is the foundational course for anyone starting their dbt journey and is designed as the first step before pursuing professional certifications like Analytics Engineering Certification.
Domain context — Analytics Engineering / Data Transformation
dbt has transformed modern data workflows by enabling analysts and engineers to apply software engineering best practices (version control, testing, documentation, deployment) to analytics code. The Fundamentals course establishes core competencies in:
- Data transformation using dbt models
- Testing data quality
- Creating documentation from code
- Using dbt Cloud for development and deployment
- Understanding the dbt ecosystem and Modern Data Stack
Topics covered
- dbt Cloud setup and initialization
- Building and executing dbt models
- The 'ref' function for model dependencies
- Writing tests for data quality assurance
- Creating and maintaining documentation
- Using dbt sources to reference raw data
- Seeds for loading reference data
- Snapshots for tracking data changes over time
- Jinja templating for dynamic SQL
- Project organization and structure
- dbt Cloud deployment pipelines
- Best practices for analytics engineering
Common job-ready skills
After completing dbt Fundamentals, you'll have foundational skills for:
- Writing and testing SQL transformation models
- Building data pipelines with dbt
- Documenting data assets
- Understanding data lineage and dependencies
- Collaborating on dbt projects
- Setting up basic dbt Cloud workflows
- Implementing data quality tests
- Writing modular, reusable dbt code
Recommended courses
- dbt Fundamentals (VS Code) - Alternative to Cloud-based version using local development
- Advanced Testing - Expands on testing strategies for Analytics Engineering Certification
- Advanced Deployment - Covers production deployment patterns for professional environments
- dbt Ecosystem Courses - Specializations on Snowflake, BigQuery, Databricks integrations
Practice exams
- dbt Fundamentals Course Completion - The course itself serves as practice and validation
- dbt Learn Certified Developer Path - Progression pathway toward professional certification
Books
- "The Fundamentals of Modern Data Stack" - Industry overviews on dbt's role
- dbt Official Documentation (docs.getdbt.com) - Comprehensive reference materials
- "Analytics Engineering with dbt" - Industry resources and thought leadership from dbt Labs
Job titles
This certification validates skills for:
- Data Analyst (foundation for analytics engineering)
- Junior Data Engineer
- Analytics Engineer (entry-level)
- Data Transformer
- Business Analyst (technical track)
- Data Quality Analyst
Salary (USD / ZAR / GBP / EUR / AUD)
Entry-level positions with dbt Fundamentals knowledge:
- USD: $60,000 - $85,000 annually
- ZAR: ~1,080,000 - 1,530,000 (est. ZAR 18x)
- GBP: ~48,000 - £68,000
- EUR: ~56,000 - €80,000
- AUD: ~95,000 - $135,000
Note: Fundamentals is a prerequisite; higher salaries typically require Analytics Engineering Certification or professional experience.
Skills validated
- SQL transformation and query writing
- dbt model development and organization
- Data testing and quality assurance
- Documentation generation and maintenance
- Basic Jinja templating
- Version control with dbt projects
- dbt Cloud navigation and deployment
- Data lineage and dependency management
- Best practices in analytics engineering
Related certifications
- dbt Analytics Engineering Certification - Professional-level credential building on fundamentals
- dbt Cloud Architect Certification - Advanced enterprise-focused certification
- Databricks Data Engineer Associate - Complementary data engineering certification
- Snowflake SnowPro Core - Cloud data platform certification
- Google Cloud Certified Associate Cloud Engineer - Cloud infrastructure foundation
- AWS Certified Data Analytics Specialty - Data analytics on AWS