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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q258-Q263):

NEW QUESTION # 258
How can you overwrite configurations for models within a package?
Choose 1 option.

A. By adding the configurations in dbt_project.yml within the package's namespace.
B. By navigating into the /dbt_packages folder and adding the configurations directly to the models.
C. After installing the package, you can apply configurations on the models in the ./target folder.
D. By specifying the configurations within the packages.yml file under the relevant package entry.

Answer: A

Explanation:
The correct answer is B: By adding the configurations in dbt_project.yml within the package's namespace.
dbt packages are installed as read-only code, meaning you should never modify files inside /dbt_packages, nor should you attempt to overwrite generated artifacts inside /target. Instead, dbt provides a clean and officially supported method for overriding or extending configurations on models from packages: using the dbt_project.yml file.
Each package comes with its own namespace, and users can override model-level configurations by referencing that namespace inside the models: section of dbt_project.yml. dbt merges project-level configurations with package-level defaults, and configurations defined in dbt_project.yml take precedence.
This is the only correct and recommended way to override settings such as materializations, tags, schema, or custom config blocks on models imported through a package.
Option A is incorrect because packages.yml is used only to declare package dependencies-not to configure package models. Option C is incorrect because the ./target folder contains compiled and ephemeral artifacts that should never be edited. Option D is incorrect because modifying code in /dbt_packages violates dbt best practices and will be overwritten each time packages are reinstalled.
Therefore, overriding configurations must be done exclusively through dbt_project.yml.

NEW QUESTION # 259
Your model has a contract on it.
When renaming a field, you get this error:
This model has an enforced contract that failed.
Please ensure the name, data_type, and number of columns in your contract match the columns in your model's definition.
| column_name | definition_type | contract_type | mismatch_reason |
|-------------|------------------|----------------|-----------------------|
| ORDER_ID | TEXT | TEXT | missing in definition |
| ORDER_KEY | TEXT | | missing in contract |
Which two will fix the error? Choose 2 options.

A. Remove order_id from the model SQL.
B. Remove order_id from the contract.
C. Add order_key to the model SQL.
D. Remove order_key from the contract.
E. Add order_key to the contract.

Answer: B,E

Explanation:
dbt model contracts enforce that the column names, data types, and number of columns defined in the contract exactly match the columns produced by the compiled SQL. If any column appears in one location (the contract or the SQL) but not in the other, dbt raises an enforcement error.
In this scenario, the error message shows:
* ORDER_ID is missing in the model definition, meaning the SQL no longer contains a column named order_id, but the contract still expects it.
* ORDER_KEY is missing in the contract, meaning the model SQL now contains a new column, but this column has not been added to the contract.
To fix the mismatch, you must remove columns from the contract that no longer exist in the SQL and add to the contract any new columns that now appear in the SQL.
Therefore:
* Option A - Remove order_id from the contract - is correct because the column no longer exists in the model SQL.
* Option D - Add order_key to the contract - is correct because the SQL now produces this column.
Options B and C incorrectly alter the wrong side of the definition, and Option E would create a mismatch in the opposite direction.
Thus, the correct fixes are A and D.

NEW QUESTION # 260
(Multiple Select)

A. Anomaly detection platforms.
B. Data integration testing frameworks (e.g., Great Expectations)
C. Tools specializing in schema change detection.
D. Continuous Integration (Cl) tools.

Answer: A,B,C

Explanation:
All of these address different aspects of advanced data validation that complement the basic tests within dbt. Cl tools (D) are involved in running these checks but are not the data validation tools themselves.

NEW QUESTION # 261
(Multiple Select)

A. Populating a lookup table with country codes.
B. Inserting large volumes of historical transactional data for backfilling purposes.
C. Defining generic tests that apply to multiple data sources.
D. Loading configuration data for production environments that differs from development settings.

Answer: A,D

Explanation:
seeds are ideal for static reference data and environment-specific configurations. Large data backfills are usually handled outside of 'seeds'. Generic tests would be defined in the tests section.

NEW QUESTION # 262
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 build --select state:modified --defer --state <path/to/artifacts>
B. dbt build --select state:modified --state <path/to/artifacts>
C. dbt run --select state:modified --state <path/to/artifacts>
dbt test --select state:modified --state <path/to/artifacts>
D. dbt build --select state:modified --defer <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: A

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 # 263
......

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