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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. Warehouse-centric transformation workflows
        • 2. Role of dbt in analytics engineering
          Topic 2: dbt Core Concepts- Models and materializations
          • 1. Ref and source functions
            • 2. Views, tables, incremental models
              - Project structure and configuration
              • 1. Packages and dependencies
                • 2. dbt_project.yml configuration
                  Topic 3: Documentation and Lineage- Data lineage understanding
                  • 1. Dependency tracking with ref()
                    • 2. Directed acyclic graph (DAG)
                      - dbt documentation system
                      • 1. Model descriptions and metadata
                        • 2. Auto-generated docs site
                          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- Running dbt in production
                                  • 1. dbt Cloud and job scheduling
                                    • 2. CI/CD integration patterns
                                      - Environments and workflows
                                      • 1. Development vs production environments
                                        • 2. Version control with Git

                                          dbt Labs dbt Analytics Engineering Certification Sample Questions:

                                          1. While working on a pull request, you realize a much better approach exists. Which actions could you take?

                                          A) Make the changes on your branch and use git push -force to overwrite the existing remote branch.
                                          B) Add new commits to the existing branch, explaining the change of direction in the comments on the pull request.
                                          C) Avoid introducing major changes during a pull request, as it hinders effective code review.
                                          D) Close the original pull request, create a new branch, and open a new pull request.


                                          2. A teammate opens a pull request with numerous changes across many files. To help with the review process, you would suggest that they:

                                          A) Resubmit the pull request as several smaller, more focused pull requests.
                                          B) All of the above.
                                          C) Provide a comprehensive summary of the intent and scope of the changes within the pull request description.
                                          D) Use detailed commit messages to explain the rationale behind each set of related changes.


                                          3. You're working in a large, enterprise-level dbt deployment. Which aspect of using dbt documentation commands could become especially important in this context?

                                          A) Developing strict documentation contribution guidelines for multiple teams and collaborators.
                                          B) All of the above.
                                          C) Version-controlling your documentation changes alongside your project code.
                                          D) Optimizing the dbt docs generate process for very large projects to minimize execution time.


                                          4. A performance-critical model depends on multiple complex transformations that would benefit from being pre-computed. Direct querying of this model should be as fast as possible. Which materialization is likely the best choice?

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


                                          5. (Multiple Select)

                                          A) Establish a naming convention in dbt that external tools can rely upon.
                                          B) Instruct dbt to rename columns rather than dropping and recreating them during updates.
                                          C) Avoid refactoring dbt models that are directly queried by external tools.
                                          D) Create views on top of dbt model tables, providing a stable abstraction layer for the Bl tools.


                                          Solutions:

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

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