DBT-AE Practice Questions: dbt Fundamentals and Architecture Domain

Correct Answer: D

Explanation: The correct answer is D. The `dbt_utils.email_format` test checks if the values in a column match a valid email format, which is exactly what's needed in this scenario. Option A checks for non-null values, option B ensures uniqueness, and option C is incorrectly configured for checking email formats. For more on custom tests, see the [dbt-utils package documentation](https://github.com/dbt-labs/dbt-utils).

Correct Answer: D

Explanation: The command `dbt test --select state:modified+` is used to run tests on models that have been modified since the last successful run, including their downstream dependencies. Option A is incorrect because it runs the models rather than testing them. Option B is partially correct, but it does not include downstream dependencies. Option C is incorrect as it selects new models, not modified ones. For more information, see [dbt's documentation on state-based selection](https://docs.getdbt.com/reference/node-selection/state-comparison).

Correct Answer: B

Explanation: The command `dbt test --select state:modified+` is used to run tests on models that have been modified, including their dependencies. The `state:modified+` selector identifies models that have changed since the last run. Option A runs tests on all models, not just modified ones. Option C uses an incorrect selector syntax. Option D is invalid as there is no `--state` flag for running tests.

Correct Answer: B

Explanation: The correct answer is B. The `not_null` test is a built-in dbt test and does not require the `dbt_utils` package. Option A is incorrect because `dbt_utils.not_null` is not a valid test; `not_null` is a core dbt test. Option C is incorrect because `dbt_utils.test_not_null` is not a recognized test name. Option D is incorrect because `unique` checks for uniqueness, not null values. For more information, see the dbt documentation on [testing](https://docs.getdbt.com/docs/building-a-dbt-project/tests).

Correct Answer: A

Explanation: To enable incremental processing in dbt, you must define a unique key in the model configuration. This key is used to identify new or updated records. The provided code snippet lacks this crucial component. A pre-hook or post-hook is not necessary for basic incremental processing. Schema tests help validate data quality but are unrelated to enabling incremental logic. For more details, refer to [dbt's documentation on incremental models](https://docs.getdbt.com/docs/building-a-dbt-project/building-models/configuring-incremental-models).

Correct Answer: A

Explanation: The correct answer is A. Converting a model to an incremental model using the `is_incremental()` function allows dbt to process only the new or changed data since the last run, which significantly improves performance for large datasets. Option B is incorrect because views do not inherently improve performance for large data processing tasks. Option C is incorrect because adding complexity can increase processing time. Option D is unrelated to performance optimization; `ref()` is used for dependency management. For more information, see the dbt documentation on [incremental models](https://docs.getdbt.com/docs/building-a-dbt-project/building-models/incremental-models).

Correct Answer: A

Explanation: The best practice is to organize dbt models into directories based on their function, such as staging, intermediate, and marts. The 'models-paths' configuration in dbt_project.yml allows you to specify which directories contain models and in what order they should be processed. This helps ensure dependencies are handled correctly. Options B and D misinterpret the purpose of these configurations, and C is incorrect because 'model-order' is not a valid configuration.

Correct Answer: B

Explanation: The best practice for deploying dbt projects is to first deploy to a staging environment where you can run tests and validate the transformations. This helps catch issues before they reach production. Option A is risky because it skips an important validation step. Option C is also risky, as it assumes off-peak hours mitigate deployment risk, which is not guaranteed. Option D is incorrect because testing should ideally occur before production deployment to prevent potential data issues.

Correct Answer: C

Explanation: The `dbt docs generate` command creates documentation for your dbt project, including descriptions for models, sources, and tests. This command will highlight any missing descriptions, helping ensure comprehensive documentation. `dbt run` is used to execute models, `dbt test` runs tests, and `dbt seed` loads data from CSV files into your database. For more details, see [dbt's documentation on documentation](https://docs.getdbt.com/docs/building-a-dbt-project/documentation).

Correct Answer: B

Explanation: The correct answer is B. The `run_started_at` Jinja variable represents the timestamp when the dbt run started, and using `strftime('%Y-%m')` formats it to the current year and month. Option A is incorrect because `current_month()` is not a valid Jinja function. Option C incorrectly formats only the month without the year, which may lead to incorrect filtering. Option D is incorrect because `current_timestamp()` is not a valid Jinja variable in dbt. For more information, see the dbt documentation on [Jinja context variables](https://docs.getdbt.com/docs/building-a-dbt-project/jinja-context/).