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[General] dbt-Analytics-Engineering Free Practice Exams & Cost Effective dbt-Analytics

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【General】 dbt-Analytics-Engineering Free Practice Exams & Cost Effective dbt-Analytics

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dbt Labs dbt Analytics Engineering Certification Exam Sample Questions (Q36-Q41):NEW QUESTION # 36
Data Quality Issue
  • A. Add specific schema tests to the model, asserting that the column in question should not contain nulls.
  • B. Inspect any filters or transformations within the model's SQL that might be unintentionally excluding data.
  • C. Run dbt test on the model and see if existing tests fail, indicating a possible regression.
  • D. Run dbt compile followed by dbt run -select model_name to isolate the model and observe its output closely.
Answer: A,B,C,D
Explanation:
This requires a comprehensive approach covering logic errors, regression tests, proactive quality checks, and isolated execution.

NEW QUESTION # 37
You discover a downstream model, dim products, references an outdated raw dataset, raw_product_archive, intended for historical analysis and not active products. What's the most appropriate corrective action?
  • A. Leave it as-is since it's not actively causing any errors currently.
  • B. Add a schema test to dim_products to catch potential errors.
  • C. Update the dim_products model to reference the active product dataset.
  • D. Delete the raw_product_archive source, so it can't be used accidentally.
Answer: C
Explanation:
Directly addressing the root cause ensures your model uses the correct source. Schema tests are safeguards but don't resolve the underlying dependency issue. Be cautious about deleting sources unless there's a very strong reason.

NEW QUESTION # 38
You're testing a model containing financial calculations. Your stakeholders require a high degree of accuracy. Which consideration is most important when designing tests for this scenario?
  • A. Ensuring tests cover a comprehensive range of input scenarios and edge cases.
  • B. Implementing a large number of generic tests to provide basic coverage.
  • C. Using floating-point-specific equality checks for calculated values.
  • D. Understanding acceptable tolerances and writing tests to check values within a defined range rather than exact matches.
Answer: A,D
Explanation:
B recognizes that financial calculations often have rounding imprecision, necessitating tolerance-based checks. C is crucial as even minor input variations can propagate into significant errors for financial models. A is generally a bad practice; D focuses on quantity, not the specific quality needed here.

NEW QUESTION # 39
You want to configure dbt to prevent tests from running if one or more of their parent models is unselected.
Which test command should you execute?
Choose 1 option.
  • A. dbt test --select "orders" --indirect-selection=empty
  • B. dbt test --select "orders"
  • C. dbt test --select "orders" --indirect-selection=cautious
  • D. dbt test --select "orders" --indirect-selection=buildable
Answer: A

NEW QUESTION # 40
You're implementing singular tests (accepted values). After providing a list of valid values, you notice some strange behavior: the test is passing even with records that contain unexpected dat a. What's the most likely issue?
  • A. A downstream process is overwriting the results after the model is built.
  • B. The accepted_values test configuration has the wrong column specified.
  • C. The model's data type isn't compatible with the accepted_values test.
  • D. Your test case is accidentally permitting null values, which bypass the check.
Answer: B,C,D
Explanation:
Each of these directly impacts the accepted_values test's effectiveness, while D is unlikely for a singular test.

NEW QUESTION # 41
......
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