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| Section | Objectives |
|---|---|
| Topic 1: Testing and Data Quality | - Built-in and custom tests
|
| Topic 2: Analytics Engineering Foundations | - Modern data stack concepts (ELT vs ETL)
|
| Topic 3: Deployment and Orchestration | - Running dbt in production
|
| Topic 4: Documentation and Lineage | - Data lineage understanding
|
| Topic 5: dbt Core Concepts | - Project structure and configuration
|
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NEW QUESTION # 160
A teammate opens a pull request with numerous changes across many files. To help with the review process, you would suggest that they:
Answer: D
Explanation:
A: Smaller PRs allow for more focused and effective reviews. B: Clear commit messages help understand the step-by-step changes within the PR. C: A summary provides a bird's-eye view for the reviewer.
NEW QUESTION # 161
Match the macro to the appropriate hook so that the correct execution steps comply with these rules:
* macro_1() needs to be executed after every dbt run.
* macro_2() needs to be executed after a model runs.
* macro_3() needs to execute before every dbt run.
* macro_4() needs to be executed before a model runs.
Answer:
Explanation:
Explanation:
Hook 1
on-run-end: "{{ macro_x() }}"
The Answer:
macro_1
Hook 2
models:
<my_dbt_project>:
post-hook: "{{ macro_x() }}"
The Answer:
macro_2
Hook 3
on-run-start: "{{ macro_x() }}"
The Answer:
macro_3
Hook 4
{{
config(
pre-hook: "{{ macro_x() }}"
)
}}
macro_4
dbt supports run-level hooks and model-level hooks.
Run-level hooks fire once per invocation, while model- level hooks fire around each individual model.
on-run-end is a run-level after hook that executes once after the entire dbt command completes.
Because macro_1() must run after every dbt run, it correctly belongs here.
The post-hook configured under the models: section runs after each model in that scope finishes building.
This matches the requirement for macro_2() to execute after a model runs.
on-run-start is a run-level before hook and fires once before dbt begins executing any models for that command, making it the right place for macro_3() which must run before every dbt run.
Finally, the pre-hook specified inside a model's config() block runs before that specific model is built.
Since macro_4() must execute before a model runs, it belongs in the pre-hook configuration.
Thus the correct mapping is:
* on-run-end # macro_1
* model post-hook # macro_2
* on-run-start # macro_3
* model pre-hook # macro_4.
NEW QUESTION # 162
You introduce a minor formatting change to a large SQL model. Afterwards, the results change unexpectedly. Which dbt-related issue might explain this, even if the SQL itself appears correct?
Answer: C
Explanation:
Whitespace matters in SQL, and CTE order is often significant even if the query might still be validly formatted.
NEW QUESTION # 163
"Sometimes columns that should have data are showing null values!" exclaims a colleague. What initial debugging steps would you suggest beyond examining the model logic itself?
Answer: D
Explanation:
Don't limit yourself to the single model in question! Data flows throughout the project, and changes elsewhere might have cascading effects.
NEW QUESTION # 164
You need to gather detailed metrics about how your dbt models are used (who runs them, frequency, common failure points, etc.). What kind of tooling would help with this?
Answer: A,B
Explanation:
B is relevant if you use dbt Cloud. C is suitable, as many observability platforms have features for tracking operational data, including dbt job metrics. A and D, while containing information, are likely too granular or require a lot of manual work.
NEW QUESTION # 165
......
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