Prepare with dbt Labs dbt-Analytics-Engineering exam torrent, pass for sure
Updated: Aug 19, 2026
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dbt Labs dbt-Analytics-Engineering Exam Overview:
| Certification Vendor: | dbt Labs |
| Exam Name: | dbt Analytics Engineering Certification Exam |
| Exam Number: | dbt-analytics-engineering-certification |
| Available Languages: | English |
| Passing Score: | Not publicly disclosed |
| Exam Price: | $100 USD (varies by region) |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | Not publicly disclosed (commonly reported ~60–70 questions) |
| Exam Format: | Multiple choice, Multiple select |
| Recommended Training: | dbt Learn dbt Documentation |
| Exam Registration: | dbt Labs official site dbt Certification Portal |
| Sample Questions: | dbt Labs dbt-Analytics-Engineering Sample Questions |
| Exam Way: | Online proctored exam (via dbt Labs certification platform / authorized proctoring provider) |
| Pre Condition: | No formal prerequisites required; strong SQL and data modeling knowledge recommended |
| Official Syllabus URL: | https://www.getdbt.com/certification |
dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Analytics Engineering Foundations | - SQL proficiency for analytics
|
| Topic 2: Deployment and Orchestration | - Environments and workflows
|
| Topic 3: Documentation and Lineage | - dbt documentation system
|
| Topic 4: Testing and Data Quality | - Built-in and custom tests
|
| Topic 5: dbt Core Concepts | - Models and materializations
|
dbt Labs dbt Analytics Engineering Certification Sample Questions:
1. Your data warehouse environment undergoes a major version upgrade, introducing changes in SQL syntax and supported functions. How would you handle the migration of dbt projects to ensure compatibility?
A) Thoroughly test all dbt models across your staging and development environments to identify necessary updates.
B) All of the above.
C) Utilize custom macros to introduce conditional logic or abstract away syntax differences between versions, if feasible.
D) Create temporary branches in your dbt projects to isolate upgrade-related code changes for each environment
2. Several models perform similar filtering and aggregation on a frequently used source table. What's the most effective way to streamline this process and improve maintainability?
A) Create a table materialization to hold the pre-processed data.
B) Replicate the filtering and aggregation logic directly within each model.
C) Create a snapshot to capture the pre-processed state of the source table.
D) Create an ephemeral model to prepare the data in a common format, referenced by downstream models.
3. (Multiple Select)
A) Using the 'defer' option to partially run a DAG and expose errors early
B) Defining source freshness thresholds to catch issues with missing tables or views-
C) Setting up a linter for your SQL files, either as part of your IDE or code editor
D) Implementing a robust suite of schema tests to validate object references-
4. You try updating a column description using its corresponding YAML file. After regenerating the docs, the update doesn't appear. Which of the following might be the cause?
A) There could be a syntax error within the updated description that dbt is silently ignoring.
B) Changes in column descriptions only update the database schema, not the project documentation.
C) The column description might need additional configuration with a test for it to render in the docs.
D) Your browser is aggressively caching the documentation site.
5. You're refactoring a complex dbt model and realize breaking it down into smaller models would improve readability. However, you're concerned about performance overhead due to the additional materializations. How would you address this concern?
A) Switch to incremental materializations for all intermediate models.
B) Utilize ephemeral materializations for intermediate steps, where appropriate_
C) Rely on source freshness checks to determine if intermediate models need to be rebuilt_
D) Profile your models to pinpoint bottlenecks and optimize those specifically.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C,D | Question # 4 Answer: A,D | Question # 5 Answer: D |
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