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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deployment and Orchestration | 15% | - CI/CD with dbt Cloud - Git version control integration - Environments (dev, staging, prod) - Jobs and scheduling in dbt Cloud |
| Topic 2: dbt Fundamentals | 15% | - dbt project structure - dbt Core vs dbt Cloud - dbt workflow and best practices |
| Topic 3: Models | 25% | - Sources and references - Materializations (table, view, ephemeral, incremental) - Seeds - Writing and managing SQL models - Snapshots |
| Topic 4: Data Transformation Techniques | 25% | - Jinja templating - Macros and packages - Common table expressions and subqueries - Refactoring and incremental models |
| Topic 5: Testing and Documentation | 20% | - Custom data tests - Documentation generation - Schema tests (unique, not_null, accepted_values, relationships) - dbt docs and DAG visualization |
dbt Labs dbt Analytics Engineering Certification Sample Questions:
You've defined a unique test on a key column within a model. When running dbt test, you encounter a surprising failure. Which of the following might be the cause?
- A. There are truly duplicate values in the column.
- B. The unique test is too strict and doesn't align with the business definition of uniqueness.
- C. An incorrect join in your model is inadvertently creating duplicate rows.
- D. Upstream data was updated unexpectedly, leading to previously non-existent duplicates.
Correct Answer: A,B,C,D 🗳️
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(Multiple Select)
- A. not_null and unique tests on primary key columns.
- B. Tests checking for row count discrepancies between source systems and target tables.
- C. Schema tests to confirm the existence of tables and columns.
- D. Tests comparing the latest data against historical baselines.
Correct Answer: A,B,C 🗳️
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You're evaluating whether to adopt an external tool that offers a visual, drag-and-drop interface for building data models. When considering this alongside dbt, what's a KEY factor to weigh?
- A. If the visual tool has advanced machine learning capabilities for data cleaning.
- B. The ease of migrating existing dbt projects into the visual tool.
- C. The ability of the tool to generate dbt-compatible SQL and integrate into your version control workflow.
- D. Whether the tool can handle the full complexity of your data transformations.
Correct Answer: C,D 🗳️
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(Multiple Select)
- A. The dbt run will succeed, but the staging model will have null values due to the missing data.
- B. Downstream models relying on the staging model will continue to function.
- C. The staging model run will fail.
- D. dbt will issue a warning but continue processing.
Correct Answer: A,C 🗳️
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You've added a new exposure to your project, but it doesn't appear in dbt docs. Here's part of your dbt_project.yml:YAML
- A. The maturity property is missing within your exposure's configuration.
- B. Exposures of type 'notebook' are not automatically detected by dbt docs generate.
- C. The owner property is not correctly formatted as an email address.
- D. You haven't run dbt docs serve after making changes to your project file.
Correct Answer: B 🗳️
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It was so exciting to receive the desired score on first attempt and this entire make possible because of your clear teaching and study tips.