dbt Labs dbt Analytics Engineering Certification : dbt-Analytics-Engineering exam

dbt-Analytics-Engineering real exams

Exam Code: dbt-Analytics-Engineering

Exam Name: dbt Analytics Engineering Certification Exam

Updated: Aug 18, 2026

Q & A: 359 Questions and Answers

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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

SectionObjectives
Topic 1: Analytics Engineering Foundations- SQL proficiency for analytics
  • 1. Data modeling in SQL
    • 2. Joins, aggregations, and window functions
      - Modern data stack concepts (ELT vs ETL)
      • 1. Role of dbt in analytics engineering
        • 2. Warehouse-centric transformation workflows
          Topic 2: Documentation and Lineage- dbt documentation system
          • 1. Auto-generated docs site
            • 2. Model descriptions and metadata
              - Data lineage understanding
              • 1. Directed acyclic graph (DAG)
                • 2. Dependency tracking with ref()
                  Topic 3: dbt Core Concepts- Project structure and configuration
                  • 1. dbt_project.yml configuration
                    • 2. Packages and dependencies
                      - Models and materializations
                      • 1. Ref and source functions
                        • 2. Views, tables, incremental models
                          Topic 4: Testing and Data Quality- Built-in and custom tests
                          • 1. Custom SQL tests
                            • 2. Generic tests (unique, not null, relationships)
                              - Data validation strategies
                              • 1. Schema testing practices
                                • 2. CI-based validation workflows
                                  Topic 5: Deployment and Orchestration- Environments and workflows
                                  • 1. Version control with Git
                                    • 2. Development vs production environments
                                      - Running dbt in production
                                      • 1. dbt Cloud and job scheduling
                                        • 2. CI/CD integration patterns

                                          dbt Labs dbt Analytics Engineering Certification Sample Questions:

                                          1. A package you depend on has released a major update with breaking changes. How might you approach the migration?

                                          A) Update your packages.yml to point to the new version and immediately refactor all your dependent models.
                                          B) Pin the package to the older version in your packages.yml file and plan a controlled migration.
                                          C) Review the release notes and the migration guide provided by the package maintainers.
                                          D) Fork the package and maintain your own custom version indefinitely.


                                          2. Select the dbt materialization that typically DOES NOT persist its results to disk:

                                          A) Snapshot
                                          B) Table
                                          C) Ephemeral
                                          D) Incremental


                                          3. (Multiple Select)

                                          A) Defining a custom source in sources.yml that selects tables from the desired subdirectory.
                                          B) Using dbt run -m to select models using a path pattern.
                                          C) Configuring separate dbt projects for each subdirectory and running them independently.
                                          D) Setting up tags strategically and using the -s flag when executing dbt commands.


                                          4. Your dbt project pulls data from a SaaS application using a third-party adapter. You observe performance issues. Where might you start optimizing?

                                          A) Check your dbt_project.yml for project-level performance settings.
                                          B) Investigate the third-party adapter's settings or documentation for potential bottlenecks.
                                          C) Review the source definitions to see if unnecessary data is being selected.
                                          D) Configure the source as an incremental materialization within your project file.


                                          5. You want to include a detailed lineage diagram in your project documentation. Which of these approaches would you likely consider?

                                          A) Use the built-in lineage functionality within dbt's standard documentation generation.
                                          B) Write a custom macro that generates a lineage diagram and include it in relevant model descriptions.
                                          C) Manually create a diagram using a separate tool and add an image reference in a model's description.
                                          D) Configure a third-party dbt package designed for enhanced lineage and visualization.


                                          Solutions:

                                          Question # 1
                                          Answer: C
                                          Question # 2
                                          Answer: C
                                          Question # 3
                                          Answer: B,D
                                          Question # 4
                                          Answer: B
                                          Question # 5
                                          Answer: B,C,D

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