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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

SectionObjectives
dbt Core Concepts- Models and materializations
  • 1. Views, tables, incremental models
    • 2. Ref and source functions
      - Project structure and configuration
      • 1. Packages and dependencies
        • 2. dbt_project.yml configuration
          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
                  Testing and Data Quality- Built-in and custom tests
                  • 1. Custom SQL tests
                    • 2. Generic tests (unique, not null, relationships)
                      - Data validation strategies
                      • 1. CI-based validation workflows
                        • 2. Schema testing practices
                          Deployment and Orchestration- Environments and workflows
                          • 1. Development vs production environments
                            • 2. Version control with Git
                              - Running dbt in production
                              • 1. dbt Cloud and job scheduling
                                • 2. CI/CD integration patterns
                                  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

                                          dbt Labs dbt Analytics Engineering Certification Sample Questions:

                                          1. You've created a macro to display upstream dependencies differently from downstream dependencies in the DAG. However, after re-generating the documentation, the visualization doesn't seem to have changed. What should you investigate?

                                          A) Update the cache expiration settings of your web browser.
                                          B) Ensure the macro is named correctly and located in the appropriate directory (macros folder) of your dbt project.
                                          C) Verify that your web browser supports the CSS and JavaScript used for custom DAG styling.
                                          D) The built-in DAG functionality might have limitations preventing this type of customization.


                                          2. You suspect discrepancies due to potential changes in upstream source tables. What's a practical first step to investigate?

                                          A) Review the dbt project's manifest.json for related changes.
                                          B) Run all dbt models and examine the logs for unusual entries.
                                          C) Contact the team responsible for managing the sources to inquire about recent updates.
                                          D) Compare the current state of the source tables against their historical snapshots.


                                          3. (Multiple Select)

                                          A) Knowledge sharing platforms or internal wikis for documenting best practices.
                                          B) Automated code linters
                                          C) Centralized dbt packages for reusable code
                                          D) Data discovery platforms to catalog available data assets


                                          4. Your team decides to use separate schemas for development and production within the same data warehouse. Which of the following dbt features are essential for managing this workflow effectively?

                                          A) dbt snapshots to compare data state between environments-
                                          B) dbt seeds to populate test data in your development schema.
                                          C) Macros and Jinja templating to dynamically switch target schemas.
                                          D) Environment variables to store environment-specific configurations.


                                          5. External Dependency

                                          A) Implement schema tests for the affected models to catch similar breakages immediately in the future.
                                          B) All of the above.
                                          C) Work with stakeholders to understand if the external change is intentional and adjust the business logic if needed.
                                          D) Introduce a temporary staging model to transform the data into a compatible structure for your existing models.


                                          Solutions:

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

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