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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q90-Q95):

NEW QUESTION # 90
Your dbt project contains models that process data with varying levels of sensitivity. Which of the following might be reasons to utilize different schemas or even different targets within your data warehouse for these data sensitivity levels?

A. To optimize query performance, as certain models might benefit from specific data warehouse configurations based on their workload.
B. To implement stricter access controls limiting which users or roles can interact with sensitive data-
C. To comply with data governance regulations that mandate separation of different data types.
D. All of the above-

Answer: D

Explanation:
A: Separate schemas or targets enhance access control granularity. B: Some data workloads might have different performance requirements- C: Compliance often necessitates structured data organization-

NEW QUESTION # 91
Which of the following scenarios might warrant you using the --no-compile flag with dbt docs generate? When you have syntax errors in your dbt models that would prevent compilation.

A. When your CI/CD pipeline requires you to generate documentation as a separate step from model compilation.
B. When you want to quickly preview documentation changes without triggering a full model build.
C. When you're deploying documentation updates to a production environment and want to minimize risks associated with model
D. recompilation.

Answer: A,C,D

Explanation:
B: The -no-compile flag speeds up docs generation when a full model build is unnecessary- C: It isolates documentation updates in production environments to reduce risk.
D: This flag provides control within CIICD pipelines when needed

NEW QUESTION # 92
A marketing team needs a model to calculate the 30-day rolling average of new customer signups. The raw signups table is very large and updated hourly. Which approach strikes the best balance between accuracy and computational efficiency?

A. A table materialization that completely rebuilds the rolling average daily.
B. An incremental model that updates the rolling average calculations only for new signup records.
C. A view materialization that recalculates the 30-day rolling average for each query.
D. An ephemeral model that calculates the rolling average within a series of complex CTEs.

Answer: B

Explanation:
Incremental models are designed for metrics like this. They minimize processing overhead while ensuring the rolling average stays up-to-date. Options A and B are computationally expensive, while D doesn't address storage for reuse.

NEW QUESTION # 93
You want to implement a macro that displays a warning icon next to models in the DAG that haven't been tested. Which of the following would be necessary to make this work?

A. A custom CSS class for the warning icon and a way to apply it dynamically using the macro.
B. The ability for the macro to query the results of test executions from the dbt run-
C. All of the above.
D. Configuration in your dbt_projectyml file to associate models with the relevant tests.

Answer: C

Explanation:
A: You'll need CSS to style the warning icon- B. The macro needs to determine if the associated tests for each model have passed or failed. C: dbt needs a way to understand which tests are related to which models for the macro to function correctly.

NEW QUESTION # 94
(Multiple Select)

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

Answer: B,C

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 # 95
......

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