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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Transformation Techniques	25%	- Common table expressions and subqueries - Refactoring and incremental models - Macros and packages - Jinja templating
Topic 2: Deployment and Orchestration	15%	- Git version control integration - Environments (dev, staging, prod) - CI/CD with dbt Cloud - Jobs and scheduling in dbt Cloud
Topic 3: dbt Fundamentals	15%	- dbt project structure - dbt workflow and best practices - dbt Core vs dbt Cloud
Topic 4: Testing and Documentation	20%	- Custom data tests - Documentation generation - Schema tests (unique, not_null, accepted_values, relationships) - dbt docs and DAG visualization
Topic 5: Models	25%	- Writing and managing SQL models - Sources and references - Materializations (table, view, ephemeral, incremental) - Seeds - Snapshots

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q41-Q46):

NEW QUESTION # 41
You need to override a source description at the model level. How would you achieve this most effectively?

A. You cannot override a source description directly in the model.
B. Utilize a Jinja macro to dynamically construct the description based on specific conditions.
C. Use the meta configuration in your model file to provide an alternative description.
D. Create a separate column in the source with a model-specific description.

Answer: C

Explanation:
The meta configuration can be used to override source descriptions and other metadata at the model level. However, make sure to check the documentation for your specific dbt version, as the exact way to do this might vary_

NEW QUESTION # 42
Data Quality Issue

A. Inspect any filters or transformations within the model's SQL that might be unintentionally excluding data.
B. Run dbt compile followed by dbt run -select model_name to isolate the model and observe its output closely.
C. Add specific schema tests to the model, asserting that the column in question should not contain nulls.
D. Run dbt test on the model and see if existing tests fail, indicating a possible regression.

Answer: A,B,C,D

Explanation:
This requires a comprehensive approach covering logic errors, regression tests, proactive quality checks, and isolated execution.

NEW QUESTION # 43
You get a warning during dbt run:WARNlNG: Found 100 rows in 'stg_customers' that will become duplicates in the 'dim_customers' target.

A. Investigate your dim_customers modeling logic to ensure a unique key is correctly used to prevent duplicates.
B. Increase the memory allocated for the database to handle the large number of duplicates.
C. It's safe to ignore this warning, as de-duplication is handled automatically by dbt.
D. Update the stg_customers source definition to include filtering logic to remove duplicate rows.

Answer: A

Explanation:
This typically indicates a logic flaw in your model creating the target table. Modifying the source or increasing memory won't resolve the core issue.

NEW QUESTION # 44
You want to run and test the models, tests, and snapshots you have added or modified in development.
Which will you invoke? Choose 1 option.
Options:

A. dbt run --select state:modified --state <path/to/artifacts>
dbt test --select state:modified --state <path/to/artifacts>
B. dbt build --select state:modified --defer <path/to/artifacts>
C. dbt build --select state:modified --state <path/to/artifacts>
D. dbt build --select state:modified --defer --state <path/to/artifacts>
E. dbt run --select state:modified --defer --state <path/to/artifacts>
dbt test --select state:modified --defer --state <path/to/artifacts>

Answer: D

Explanation:
The goal in this scenario is:
* Select only models, tests, and snapshots that were modified in development, using:state:modified
* Use already-built production objects whenever possible, so development does not need to rebuild everything. This is done with:--defer
* Compare development code against production artifacts, which requires:--state <path/to/artifacts>
* Run everything (models + tests + snapshots) in a single command. This is exactly what dbt build does.
* dbt build = run models + run tests + run snapshots + run seeds.
Putting it all together, the correct command is:
dbt build --select state:modified --defer --state <path/to/artifacts>
This single command satisfies all requirements:
* It runs only modified resources.
* It uses the production state artifacts for comparison.
* It defers to production-built models where possible.
* It runs all resource types automatically.
Why the other options are incorrect:
* A # Missing --state, so state:modified cannot function.
* B # Splits run + test separately; question asks which single command you will invoke.
* D # Missing --defer, which defeats the purpose of using production objects.
* E # Also missing --defer.
Thus, Option C is the only correct answer.

NEW QUESTION # 45
dbt Model Snippet:SQL

A. Making sure the source table fct_orders contains the expected columns.
B. Checking that the date_part() function is compatible with your database-
C. Ensuring the grains variable is defined in dbt_project.yml or a macro.
D. Validating that the column names generated by the Jinja loop would be valid SQL identifiers.

Answer: C

Explanation:
Compilation errors often mean undefined variables or incorrect Jinja syntax. The rest are potential issues but less likely to break at the compilation stage.

NEW QUESTION # 46
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